MSEP 520 : RESEARCH DESIGN AND METHODS...Kwame Nkrumah University of Science & Technology, Kumasi,...
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Kwame Nkrumah University of Science & Technology, Kumasi, Ghana MSEP 520 : RESEARCH DESIGN AND METHODS Dr. Emmanuel Kwesi Arthur Department of Materials Engineering, College of Engineering, Kwame Nkrumah University of Science and Technology © January 2020
Transcript of MSEP 520 : RESEARCH DESIGN AND METHODS...Kwame Nkrumah University of Science & Technology, Kumasi,...
Kwame Nkrumah University of Science & Technology, Kumasi, Ghana
MSEP 520 : RESEARCH DESIGN AND METHODS
Dr. Emmanuel Kwesi Arthur
Department of Materials Engineering,
College of Engineering,
Kwame Nkrumah University of Science and Technology
© January 2020
2 1/31/2020
able to understand the different types of research methodology
able to be aware of the different data collection tools.
able to understand sampling design Evaluating scientific papers Consulting scientific Data Bases and searching for
information Criticizing a scientific paper Writing a scientific paper Publishing a scientific paper
Learning Objectives
By the end of this lecture you should be:
What We‟re NOT Going to Learn in this Course
Specific experimental techniques and methods.
A full treatment of statistical methods of analysis.
Explicit reviews of scientific article.
Lecture Outline:
1. Overview of the Research Process 2. Research Methods
1. Quantitative & Qualitative Research Strategies 2. Experimental Designs
3. Sampling Methods and Statistical Analysis of Data 4. Literature Search 5. Report Writing, Data Collection & Presentation 6. Review of Scientific article 7. Proposal writing 8. Thesis writing
Copyright: David Thiel 2009
Grading
5 1/31/2020
Format:
Grading:
Scientific article review 10%
Assignments and Presentations 15%
Take home exams 15%
Final Exams 60%
READING LIST
www.knust.edu.gh
Aaker, D.A., Kumar, V. and Day, G.S. (1998). Marketing research. 6th
edition. John Wiley, New York. Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin M. (2013).
Business Research Methods, International edition ; South- Western, Cengage Learning publishers, Australia/New Zealand.
Cooper, R. D. & Schindler, S. P. (2008). Business Research
Methods. Boston: Irwin McGraw Hill. Bryman, A. & Bell, E. (2007). Business Research Methods, USA:
Oxford University Press.
Research Process
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One of the primary goals of academic training is to learn how to learn, i.e., to learn how to continuously absorb new knowledge.
What is the primary goal of academic training?
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The process of exploring the unknown, studying and learning new things, building new knowledge about things that no one has understood before - that is what we think of as performing research.
What do you understand by research?
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The activity of a diligent and systematic inquiry or investigation in an area, with the objective of discovering or revising facts, theories, applications etc. The goal is to discover and disseminate new knowledge
Copyright: David Thiel 2009
Something new to humanity (not just new to you or your group).
Research Defined and Described
“Research is the systematic approach to obtaining and confirming new and reliable knowledge”
– Systematic and orderly (following a series of steps) – Purpose is new knowledge, which must be reliable This is a general definition which applies to all disciplines
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Notice that: “… truth was not used in the definition of research” “This concept of truth is outside of the productive realm of thinking by researchers”
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Research Ethics
Code of Ethics: first published by ASA in 1971
1. Maintain objectivity and integrity in research
2. Respect subject‟s right to privacy and dignity
3. Protect subjects from personal harm
4. Preserve confidentiality
5. Seek informed consent
6. Acknowledge research collaboration and assistance
7. Disclose all sources of financial support
© 2018 E. K. Arthur
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Research Ethics
█ Confidentiality – Supreme Court has failed to clarify rights of
scholars
• Research Funding
– Funding source should not taint objectivity of research
• Value Neutrality
– Researchers should not allow personal feelings to influence interpretation of data
© 2018 E. K. Arthur
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Regardless of the type of research, it is critical that it must be reliable
Research is not
Accidental discovery : 1. Accidental discovery may occur in
structured research process 2. Usually takes the form of a phenomenon
not previously noticed 3. May lead to a structured research
process to verify or understand the observation
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Research is not … cont.
Data Collection an intermediate step to gain reliable
knowledge collecting reliable data is part of the
research process
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Research is not … cont.
Searching out published research results in libraries (or the internet) This is an important early step of research The research process always includes
synthesis and analysis But, just reviewing of literature is not
research
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Research is…
1. Searching for explanation of events, phenomena, relationships and causes –What, how and why things occur –Are there interactions?
2. A process – Planned and managed – to make the
information generated credible – The process is creative – It is circular – always leads to more
questions
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•All well designed and conducted research has potential application. •Failure to see applications can be due to:
–Users not trained or experienced in the specialized methods of scientific research and reasoning –Researchers often do not provide adequate interpretations and guidance on applications of the research
• Researchers are responsible to help users understand research implications
(How?)
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Why do research?
Validate intuition
Improve methods
Demands of the Job
For publication
Key Players
The researcher The supervisor The evaluator
Researcher
Supervisor(s)
Evaluator(s)
The Research Team
The Researcher
Discuss with your supervisor what supervision and work schedule is good for you and them.
Discuss the topic and timetable with the supervisor
Stick with the schedule and don’t disappear from the supervisor’s radar
Keep systematic records of work Submit written material with enough time for
the supervisor to read it.
The Researcher
Discuss the final submission details with the supervisor
Don’t ignore criticisms or guidance from the supervisor
Make sure you don’t do anything illegal Remember you are the driver Let the supervisor know of any problems Do your best.
The Supervisor
Know the rules and standards of the organization regarding research
Make sure the supervisees know the rules and standards
Discuss dates and work schedules Give needed guidance Continuously update skill set Schedule regular meetings
Assignment 1: Outline the rules and standards of the KNUST‟s graduate school regarding research.
Scientific Research
Research
Research is also a process of inquiry. It entails the following steps:
1. Posing a question
2. Developing a procedure to answer that question
3. Following that procedure.
However,
Not all research is scientific. Why?
Scientific Research
Scientific research is the process of inquiry in which we:
1. Pose a question about the physical world
2. Develop a set of procedures using the rational process that if followed, would convincingly answer that question
3. Plan to make appropriate empirical observations
4. Rationally interpret the empirical observation to arrive at a conclusion.
Research Settings
“Artificial” world – laboratory setting controlled setting
Real world - natural setting naturalistic observation
What are the advantages and disadvantages of each setting?
Development of Research Skills
Learning how to conduct good research: New skills (that many people do not have) Better understanding and interpretation of
the literature Recognize new questions that need
investigation Objectivity is the key element of research
Research Classifications
System #1: Basic research Applied research
System #2: Quantitative research Qualitative research
System #3: Experimental research Non-experimental research
Basic vs Applied Research
•Basic – to determine or establish fundamental facts and relationships within a discipline or field of study. Develop theories … (examples in science?) •Applied – undertaken specifically for the purpose of obtaining information to help resolve a particular problem •The distinction between them is in the application
–Basic has little application to real world policy and management but could be done to guide applied research
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System #1:
Basic vs. Applied Research
Basic Pure, fundamental
research
Discovery of new knowledge; theoretical in nature
Takes many years for the results of basic research to find some practical utility
Applied Central purpose to
solve an immediate problem
Improved products or processes
Infers beyond the group or situation studied
Interpretation of results relies upon Basic research
System #1:
Quantitative vs. Qualitative
Qualitative Discover underlying meanings
and patterns of relationships without using or developing mathematical models.
Generally non-numerical data Qualitative methods involve
fieldwork which could include interviews or personal observations
Usually small sample sizes Experiments not necessarily
repeatable
System #2:
Quantitative Develop models, theories,
and hypotheses describing a phenomenon
Numerical, measurable data
It involves measuring something that will help develop the model/theory/ hypothesis
Large samples needed
Experiments are repeatable
Experimental vs. Nonexperimental
Experimental IVs and DVs Cause-and-effect Extraneous variable
controls 3 fundamental
characteristics 1. At least 1 active IV 2. Extraneous var
controls 3. Observation of the
DV response to the IV
Nonexperimental 1. Causal-comparative
2. Descriptive
3. Correlational
4. Historical
System #3:
Steps to Experimental Research
1. Identifying the research question or problem area
2. Initial review of literature 3. Distilling the question to a specific
research problem 4. Continued review of literature 5. Formulation of hypotheses 6. Determining the basic research approach 7. Identifying the population and sample
Steps to Experimental Research
8. Designing data collection plan 9. Selecting or developing specific data
collection instruments or procedures 10. Choosing the method of data analysis 11. Implementing the research plan 12. Preparing the research report
Research Methods
Procedures for collecting data, formulating a hypothesis, testing a hypothesis, interpreting results, and drawing conclusions
Research and research methods
Research methods are split broadly into quantitative and qualitative methods
Which you choose will depend on your research questions your underlying philosophy of research your preferences and skills
The Scientific Method
Systematic; cyclic; series of logical steps. 1) Identifying the problem 2) Formulating a hypothesis 3) Developing the research plan 4) Collecting and analyzing the data 5) Interpreting results and forming
conclusions
Disseminate your solution
New Questions Arise
Results Interpreted
Data Collected
Question Identified
Hypotheses Formed
Research Plan
Closed-loop conceptualization of the research process (Drew, Hardman, and Hart, 1996)
2) Formulating a Hypothesis
Hypothesis: A belief or prediction of the eventual outcome of
the research A concrete, specific statement about the
relationships between phenomena Based on deductive reasoning 2 types of hypotheses:
Null hypothesis (HO)
All is equal; no differences exist Alternative (research) hypothesis (HA)
Usually specific and opposite to the null
4) Collecting and Analyzing the Data
Following all the pre-determined protocols Time in the lab collecting data Analyzing the composite data Controlling the environment
Easiest part of the process… However, sometime the most time-
consuming part of the process…
Types of Research Data Collection Techniques
5) Interpreting Results and Forming Conclusions
DATA ANALYSIS IS NOT AN END IN ITSELF! Does the evidence support or refute the original
hypotheses? Accept or reject the hypotheses Conclusions should be drawn:
Develop new hypotheses to explain the results Inferences are typically made beyond the specific study
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
DEVELOPING HYPOTHESIS AND
RESEARCH QUESTIONS
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Introduction
Processes involved before formulating the hypotheses.
Definition
Nature of Hypothesis
Types
How to formulate a Hypotheses in
Quantitative Research
Qualitative Research
Testing and Errors in Hypotheses
Summary
DEVELOPING
HYPOTHESES
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RESEARCH
QUESTIONS
The research structure helps us create research that is :
Quantifiable Verifiable Replicable Defensible
Corollaries among the model, common sense & paper format
Model
Research Question
Develop a Theory
Identify Variables (if applicable)
Identify hypotheses
Test the hypotheses
Evaluate the Results
Critical Review
Common Sense
Why
Your Answer
How
Expectations
Collect/Analyze data
What it Means
What it doesn‟t Mean
Paper Format
Intro
Intro
Method
Method
Results
Conclusion
Conclusion
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Most research projects share the same general structure, which
could be represented in the shape of an hourglass.
The “Hourglass” notion of research
BEGIN WITH BROAD
QUESTIONS NARROW
DOWN, FOCUS IN
OPERATIONALIZE
OBSERVE
ANALYZE
DATA
REACH CONCLUSIONS
GENERALIZE BACK TO
QUESTIONS
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Some of the methods that are included for research formulation are
Where does the problem origination or discovery begin?
Previous Experience
Triggered Interest
Potential problem
fields
Criteria of problems and problem statement
Goals & Planning
Search, Explore & Gather the Evidence
Generate creative and logical alternative solutions
Making the educated guess- the hypothesis!
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Definitions of hypothesis “Hypotheses are single tentative guesses, good hunches – assumed for use in devising theory or planning experiments intended to be given a direct experimental test when possible”. (Eric Rogers, 1966) “A hypothesis is a conjectural statement of the relation between two or more variables”. (Kerlinger, 1956) “Hypothesis is a formal statement that presents the expected relationship between an independent and dependent variable.”(Creswell, 1994) “A research question is essentially a hypothesis asked in the form of a
question.”
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Definitions of hypothesis
“It is a tentative prediction about the nature of the relationship between two or more variables.” “A hypothesis can be defined as a tentative explanation of the research problem, a possible outcome of the research, or an educated guess about the research outcome.” (Sarantakos, 1993: 1991) “Hypotheses are always in declarative sentence form, an they relate, either generally or specifically , variables to variables.” “An hypothesis is a statement or explanation that is suggested by knowledge or observation but has not, yet, been proved or disproved.” (Macleod Clark J and Hockey L 1981)
DEVELOPING
HYPOTHESES
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RESEARCH
QUESTIONS
Nature of Hypothesis
The hypothesis is a clear statement of what is intended to be investigated. It should be specified before research is conducted and openly stated in reporting the results. This allows to:
Identify the research objectives Identify the key abstract concepts involved in the research Identify its relationship to both the problem statement and
the literature review
A problem cannot be scientifically solved unless it is reduced to hypothesis form
It is a powerful tool of advancement of knowledge, consistent with existing knowledge and conducive to further enquiry
DEVELOPING
HYPOTHESES
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It can be tested – verifiable or falsifiable
Hypotheses are not moral or ethical questions
It is neither too specific nor to general
It is a prediction of consequences
It is considered valuable even if proven false
Nature of Hypothesis
DEVELOPING
HYPOTHESES
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RESEARCH
QUESTIONS
An Example… Imagine the following situation:
You are a nutritionist working in a zoo, and one of your responsibilities is to develop a menu plan for the group of monkeys. In order to get all the vitamins they need, the monkeys have to be given fresh leaves as part of their diet. Choices you consider include leaves of the following species: (a) A (b) B (c) C (d) D and (e) E. You know that in the wild the monkeys eat mainly B leaves, but you suspect that this could be because they are safe whilst feeding in B trees, whereas eating any of the other species would make them vulnerable to predation. You design an experiment to find out which type of leaf the monkeys actually like best: You offer the monkeys all five types of leaves in equal quantities, and observe what they eat.
There are many different experimental hypotheses you could formulate for the monkey study. For example:
When offered all five types of leaves, the monkeys will preferentially feed on B leaves.
This statement satisfies both criteria for experimental hypotheses. It is a
•Prediction: It predicts the anticipated outcome of the experiment
•Testable: Once you have collected and evaluated your data (i.e. observations of what the monkeys eat when all five types of leaves are offered), you know whether or not they ate more B leaves than the other types.
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Incorrect hypotheses would include:
When offered all five types of leaves, the monkeys will preferentially eat the type they like best.
This statement certainly sounds predictive, but it does not satisfy the second criterion: there is no way you can test whether it is true once you have the results of your study. Your data will show you whether the monkeys preferred one type of leaf, but not why they preferred it (i.e., they like it best). I would, in fact, regard the above statement as an assumption that is inherent in the design of this experiment, rather than as a hypothesis.
When offered all five types of leaves, the monkeys will preferentially eat B leaves because they can eat these safely in their natural habitat.
This statement is problematic because its second part ('because they can eat these safely in their natural habitat') also fails to satisfy the criterion of testability. You can tell whether the monkeys preferentially eat baobab leaves, but the results of this experiment cannot tell you why.
In their natural habitat, howler monkeys that feed in B trees are less vulnerable to predation than monkeys that feed on A, C, D, or E.
DEVELOPING
HYPOTHESES
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RESEARCH
QUESTIONS
This is a perfectly good experimental hypothesis, but not for the experiment described in the question. You could use this hypothesis if you did a study in the wild looking at how many monkeys get killed by predators whilst feeding on the leaves of A, B etc. However, for the experimental feeding study in the zoo it is neither a prediction nor testable.
When offered all five types of leaves, which type will the monkeys eat preferentially?
This is a question, and questions fail to satisfy criterion #1: They are not predictive statements. Hence, a question is not a hypothesis.
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Types of Hypotheses
NULL HYPOTHESES Designated by: H0 or HN Pronounced as “H oh” or “H-
null”
ALTERNATIVE HYPOTHESES
Designated by: H1 or HA
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
The null hypothesis represents a theory that has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved.
Has serious outcome if incorrect decision is made!
The alternative hypothesis is a statement of what a hypothesis test is set up to establish.
Opposite of Null Hypothesis.
Only reached if H0 is rejected.
Frequently “alternative” is actual desired conclusion of the researcher!
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
EXAMPLE
In a clinical trial of a new drug, the null hypothesis might be that the new drug is no better, on average, than the current drug.
We would write H0: there is no difference between the two drugs on average.
The alternative hypothesis might be that:
the new drug has a different effect, on average, compared to that of the current drug.
We would write H1: the two drugs have different effects, on average.
the new drug is better, on average, than the current drug.
We would write H1: the new drug is better than the current drug, on average.
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
We give special consideration to the null hypothesis…
This is due to the fact that the null hypothesis relates to the statement being tested, whereas the alternative hypothesis relates to the statement to be accepted if / when the null is rejected.
The final conclusion, once the test has been carried out, is always given in terms of the null hypothesis. We either 'reject H0 in favor of H1' or 'do not reject H0'; we never conclude 'reject H1', or even 'accept H1'.
If we conclude 'do not reject H0', this does not necessarily mean that the null hypothesis is true, it only suggests that there is not sufficient evidence against H0 in favor of H1; rejecting the null hypothesis then, suggests that the alternative hypothesis may be true.
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Formulating a hypothesis …is important to narrow a question down to one that can reasonably be studied in a research project.
The formulation of the hypothesis basically varies with the kind of research project conducted:
QUALITATIVE QUANTITATIVE
DEVELOPING
HYPOTHESES
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RESEARCH
QUESTIONS
Can also be divided into:
Observation
Theory
Tentative hypothesis
Pattern
Deductive
Inductive Theory
Hypothesis
Observation
Confirmation
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Qualitative Approach The use of Research Questions as opposed to objectives or hypothesis, is more frequent.
Characteristics Use of words- what or how. Specify whether the study: discovers, seeks to understand, explores or describes the experiences. Use of non-directional wording in the question. These questions describe, rather than relate variables or compare groups. The questions are under continual review and reformulation-will evolve and change during study. The questions are usually open-ended, without reference to the literature or theory. Use of a single focus.
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
The rules of Qualitative research
Kleining offers four rules for a scientific and qualitative process of approaching understanding to reality.
Rule 1 (refers to subject / researcher)
"Prior understandings of the phenomenon to be researched should be seen as provisional and should be transcended with [the discovery of] new information with which they are not consistent." (1982: 231)
Rule 2 (refers to the object of study)
"The object is provisional; it is only fully known after the successful completion of the process of discovery." (1982: 233)
Rule 3 (refers to action in relation to the subject of research, hence to data collection)
"The object should be approached from "all" sides; rule of the maximum variation of perspectives." (1982: 234)
Rule 4 (refers to the evaluation of information gathered, hence to data analysis)
"Analysis of the data for common elements." (1982: 237)
DEVELOPING
HYPOTHESES
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RESEARCH
QUESTIONS
Quantitative Approach
In survey projects the use of research questions and objectives is more frequent
In experiments the use of hypotheses are more frequent
Represent comparison between variables
relationship between variables
Characteristics
The testable proposition to be deduced from theory.
Independent and dependent variables to be separated and measured separately.
To be either writing-questions, or objectives or hypotheses, but not a combination.
Consider the alternative forms for writing and make a choice based on the audience for the research
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Generation of Research Hypothesis
Problem statements become research hypotheses when
constructs are operationalized
Initial Ideas
(often vague and general)
Initial
observations Search of existing
research literature
Operational definitions
of constructs
Statement of the problem
Research hypothesis
(a specific deductive prediction)
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Example:
Consider the example of a simple association between two variables, Y and X. 1. Y and X are associated (or, there is an association between Y
and X).
2.Y is related to X (or, Y is dependent on X).
3.As X increases, Y decreases (or, increases in values of X appear to effect reduction in values of Y).
DEVELOPING
HYPOTHESES
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RESEARCH
QUESTIONS
The first hypothesis provides a simple statement of association between Y and X. Nothing is indicated about the association that would allow the researcher to determine which variable, Y or X, would tend to cause the other variable to change in value.
The second hypothesis is also a simple statement of association between Y and X, but this time it may be inferred that values of Y are in some way contingent upon the condition of the X variable.
The third hypothesis is the most specific of the three. Not only does it say that Y and X are related and that Y is dependent on X for its value, but it also reveals something more about the nature of the association between the two variables.
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Testing & Challenging
The degree of challenge to the hypothesis will depend on the type of problem and its importance. It can range from just seeking “a good enough” solution to a much more rigorous challenge.
The term “challenging” may include
There are two possibilities
1. Nothing Happened
2. Something Happened
the Null Hypothesis - Ho
the Alternative Hypothesis - H1
Verification
Justification
Refutability
Validity
Rectification
Repeatability
Falsification
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Hypothesis testing is a four-step procedure: 1. Stating the hypothesis (Null or Alternative)
2. Setting the criteria for a decision
3. Collecting data
4. Evaluate the Null hypothesis
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
sick
sick
well
well
Get scared for nothing!
WRONG-Type I error
You‟re really not sick! RIGHT
You are sick. Doc confirms it
RIGHT
Doc missed your real illness!
WRONG-Type II error.
Errors in Hypotheses
Two types of mistakes are possible while testing the hypotheses.
Type I
Type II
Small example: Your actual health
Wh
at
do
c s
ays
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Type I Error:
A type I error occurs when the null hypothesis (H0) is wrongly rejected.
For example, A type I error would occur if we concluded that the two drugs produced different effects when in fact there was no difference between them.
Type II Error:
A type II error occurs when the null hypothesis H0, is not rejected when it is in fact false.
For example: A type II error would occur if it were concluded that the two drugs produced the same effect, that is, there is no difference between the two drugs on average, when in fact they produced different ones.
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
To generalize:
Decision
Reject H0 Don't reject H0
H0 Type I Error Right Decision
H1 Right Decision Type II Error
Truth
A type I error is often considered to be more serious, and therefore more
important to avoid, than a type II error.
DEVELOPING
HYPOTHESES
&
RESEARCH
QUESTIONS
Summary
“Research questions and hypotheses become “signposts” for explaining the purpose of the study & guiding the research…”, Creswell
A hypothesis is an explanation, tentative and unsure of itself, for specific phenomena about which you have questions.
A well-crafted hypothesis very often suggests the best way to perform the research and gives you clues as to your research design.
There are different types of hypotheses.
deductive
inductive
Research Hypothesis can either be non-directional or directional. There exists a hypothesis that is opposite of the positively stated one, i.e. the null hypothesis
Thus to conclude it would be fitting to say “hypothesis is perhaps the most powerful tool, man has invented to achieve dependable knowledge” – Fred Kerlinger…
CONTENT
Research design Sampling methods
Data collection methods
Measurement and scaling
Data analysis Interpretation of results and writing Research proposal development
TERMINOLOGIES
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SETH ETUAH (PHD)
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Population: This is the set of all the individuals of interest in a particular study. It is the entire group one wishes to study. Populations may be quite large. It may vary in size, from large to small.
Sample: It is a set of individuals selected from a population usually intended to represent the population
Representative Sample characteristics similar to population opposite of “biased sample”
Random Sample: equal chance of being selected
Why the need to sample? It is normally impossible to examine every single individual in a
population. Hence there is the need to select a smaller, a manageable group to represent the entire population.
Example: A sample of producers/consumers/retailers/wholesalers etc.
Parameter: It is a numerical value that describes a population. It may be obtained from a single measurement or set of measurements from the population. Eg. Mean age in census, etc.
Statistic: It is a numerical value that describes a sample. It may be obtained from a single measurement or derived from a set of measurement from a sample. Eg. Sample mean, std. etc
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Sampling Error: It is the discrepancy or amount of error that exist between a sample statistic and the corresponding
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Population parameter. It is normally occurring difference between a statistic and a parameter.
It is normally referred to as “margin of error” i.e. when sample statistic is used to represent a population parameter, there will always be a “margin of error”.
Data: These are measurements or observations. The raw,
unorganized facts that need to be processed.
A Data Set: It is a collection of measurement or observations.
Datum: It is a single measurement or observation. It is normally called a score or a raw data.
TYPES OF DATA
1. Primary Data
It is a raw data collected for the first time.
Normally through survey interviews, focus group
discussions etc.
It is often collected from the field.
It is original in nature that focuses the desire of researcher.
It is often elaborated and used only by the investigator.
Secondary Data
It is a processed data.
It is often collected from previous records or official records
such as accredited institutional sources etc.
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Secondary data may not serve all purposes as desired.
It is not elaborate but concise.
Unlike primary data which is used only by the researcher, it may be used by anyone.
All secondary data was initially primary but primary data may not be secondary data.
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DR. SETH ETUAH
Before data collection, one should be mindful of the following: The aim of the investigation Knowledge about the sources of collection Method of collection Choice of units Proper sampling Degree of accuracy
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STATISTICAL METHODS
Descriptive statistics: They are the statistical procedures that are used to summarize, organize and simplify data. Examples: Averages, Graphs (line, chart, histogram etc).
Inferential Statistics: It consists of techniques that allow us to study sample and make generalization about the populations from which they were selected.
Variable: It is a characteristic or something that can change or have different values for different individuals.
Example; temperature, height, weight , yield, etc.
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Constant: It is a characteristic or condition that does not vary or change but is the same for every individual.
Discrete Variable: A variable that is not divisible into
infinite number of fractional parts.
It consists of separate indivisible categories.
It consists of whole numbers that vary in countable steps. Example: number of children in a family, household size etc.
Continuous variable: This is variable that is divisible into infinite number of fractional parts. Example: weight of individuals, heights of individuals.
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Independent variable: A variable that is manipulated by the researcher.
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The dependent variable is the property you are trying to explain; it is always the object of the research.
Dependent variable: A variable observed for changes that may occur as a result of a manipulation.
The independent variable is often seen influencing, directly or indirectly, the dependent variable.
• Example: Y =aX +C
Y is the dependent variable X is the independent (explanatory variable),
a is the coefficient (a constant attached to an independent
variable)
C is the constant.
Definition of variables:
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Law of the single variable:
there will always be uncontrollable influences
Extraneous Variables: must be controlled to isolate the effect of the IV on the DV
Confounding Variables = extraneous variables which have co-varied with the IV
=outside influence that changes the effect of a dependent and independent variable
Confounding variables can ruin an experiment and produce useless results
What is a Controlled Experiment ?
A Controlled Experiment means that only ONE independent Variable is being tested at a time!!!
This allows the scientists to evaluate the results of the one thing being tested!!!
More Definitions
Experimental Treatments
Alternative manipulations of the independent variable being investigated
Experimental Group
Group of subjects exposed to the experimental treatment
Control Group
Group of subjects exposed to the control condition
Not exposed to the experimental treatment
More Definitions
Test Unit Entity whose responses to experimental treatments
are being observed or measured
Randomization Assignment of subjects and treatments to groups is
based on chance
Provides “control by chance”
Random assignment allows the assumption that the groups are identical with respect to all variables except the experimental treatment
In sampling, we gather data on an entire “population” by measuring only a subset of that population, known as the sample.
A population consists of all of the individual elements in a defined area.
Sampling Design
Are there too many people in the group that you are studying?
Are you limited in time and resources?
If you answered yes to one or both questions, you might want to select a sampling design to carry out your study.
Sampling Design
A simple random sample is a selection of individuals chosen so that each point in the population has an equal chance of being selected.
Each item in a “population” can be assigned a number. Then the simple random sample can be selected by using a random number table or a random number generator (using a computer).
Sampling Design
A well-defined sample has the same characteristics as the population as a whole
It is very important to:
define the population before selecting the sample
decide the size of the sample.
How big should a sample be?
The bigger the sample size the greater will be its accuracy.
Once a researcher decides on a sample, he needs to obtain data from this sample.
Sampling Design
What quant researchers worry about
Is my sample size big enough?
Have I used the correct statistical test?
Are my results generalisable?
Are my results/methods/results reproducible?
Am I measuring things the right way?
What’s wrong with quant research?
Some things can‟t be measured – or measured accurately
Doesn‟t tell you why
Can be impersonal – no engagement with human behaviours or individuals
Data can be static – snapshots of a point in time
Can tell a version of the truth (or a lie?) “Lies, damned lies and statistics” – persuasive power of numbers
The data were collected using an internet
questionnaire survey. Six hundred Saudi engineering
companies were selected from 2,002 companies
obtained from the Chamber of commerce database.
Determine the used research method, sample and
population in the above statement?
Quiz
Independent Measures Design An independent measures design is a research method in
which multiple experimental groups are used and participants are only in one group.
Each participant is only in one condition of the independent variable during the experiment.
The advantage of this is that there are no order effects, which is when participants behave differently due to the order of conditions performed, due to the factors such as boredom or fatigue.
The disadvantage is that there is the potential for error due to individual differences between the groups of participants.
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Class Assignment 2 Researchers conducted an independent measures design experiment in a local
coffee bar, investigating whether receiving physical contact from someone increases their rating on friendliness. The experiment took place between 11am and 2pm on a Wednesday. As members of the public left the coffee bar after paying, some were touched lightly on the upper arm by the cashier, whereas others were not. Outside the coffee bar, members of the public were asked how friendly they thought the staff were on a scale of 1 („not very friendly‟) to 10 („extremely friendly‟).
a) What is the independent variable in this study? (1)
b) Write a two tailed hypothesis for this study. (4)
c) Identify the sampling technique used to obtain participants for this study.
d) Suggest one weakness with the sampling method used in this study. (2)
e) What is an „independent measures design‟? (2)
f) Give one advantage and one disadvantage of using an independent measures design in this study.
g)Describe how you would control one variable in this study. (2)
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Assignment 3 A researcher has conducted a matched pairs design experiment to
investigate whether chewing gum influences concentration. Participants were matched on age and gender. She firstly recorded how many changes were detected in a „spot-the-difference‟ puzzle by people not chewing gum when completing the task, then compared this to the matched group who did chew gum during the task. The results were then compared.
a) Write a research aim for this experiment. (2)
b) Write a null hypothesis for this experiment. (4)
c) Outline one strength and one weakness of using a matched pairs design in this experiment. (6)
d) Describe an alternative experimental design and one strength of using this design instead of a matched pairs design. (6)
e) What is the Independent variable and dependent variable in this investigation? (2)
f) Outline how you could select a sample that would be representative. (3)
g) Explain how participant variables could bias the sample in this study. (3)
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Example
Question: Does salted drinking water affect blood pressure (BP) in mice?
Experiment:
1. Provide a mouse with water containing 1% NaCl.
2. Wait 14 days.
3. Measure BP.
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Comparison/control
Good experiments are comparative.
Compare BP in mice fed salt water to BP in mice fed plain water.
Compare BP in strain A mice fed salt water to BP in strain B mice fed salt water.
Ideally, the experimental group is compared to concurrent controls (rather than to historical controls).
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Replication
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Why replicate?
Reduce the effect of uncontrolled variation (i.e., increase precision).
Quantify uncertainty.
A related point:
An estimate is of no value without some statement of the uncertainty in the estimate.
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Randomization
Experimental subjects (“units”) should be assigned to treatment groups at random.
At random does not mean haphazardly.
One needs to explicitly randomize using
• A computer, or
• Coins, dice or cards.
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Why randomize?
Avoid bias. For example: the first six mice you grab may have intrinsicly
higher BP.
Control the role of chance. Randomization allows the later use of probability theory, and
so gives a solid foundation for statistical analysis.
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Stratification Suppose that some BP measurements will be made
in the morning and some in the afternoon.
If you anticipate a difference between morning and afternoon measurements:
Ensure that within each period, there are equal numbers of subjects in each treatment group.
Take account of the difference between periods in your analysis.
This is sometimes called “blocking”.
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Is the arrangement of experimental units in groups that are similar to one another
Example
• 20 male mice and 20 female mice.
• Half to be treated; the other half left untreated.
• Can only work with 4 mice per day.
Question: How to assign individuals to treatment groups and to days?
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An extremely bad design
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Randomized
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A stratified design
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Randomization and stratification
If you can (and want to), fix a variable.
e.g., use only 8 week old male mice from a single strain.
If you don’t fix a variable, stratify it.
e.g., use both 8 week and 12 week old male mice, and stratify with respect to age.
If you can neither fix nor stratify a variable, randomize it.
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Summary
Unbiased
Randomization
Blinding
High precision
Uniform material
Replication
Blocking
Simple
Protect against mistakes
Wide range of applicability
Deliberate variation
Factorial designs
Able to estimate uncertainty
Replication
Randomization
Characteristics of good experiments:
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SCALES OF MEASUREMENT Nominal, Ordinal, Interval, and Ratio scales
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SETH ETUAH (PHD)
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1.Nominal scale: Consists of a set of categories that have different names but are not differentiated in terms of magnitude and direction. Example: Gender of person on questionnaire, nominal scale of two categories Occupation: sales professionals, skilled trade and others (specify). 2.Ordinal scale: It consists of a set of categories that are organized in an ordered sequence. Measurement on an ordinal scale ranks observations in terms of size of magnitude. Examples: Series of ranks: 1st, 2nd, 3rd and so on. In perception studies, we have ordinal scales such as LIKERT scale University degree/class
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3. Interval scale consists of ordered categories that are all intervals of exactly the same size.
SETH ETUAH (PHD)
14
Equal differences between numbers on the scale reflect equal differences in magnitude.
The zero point on an interval scale is arbitrary The ratio between two numbers is not meaningful. Example: Temperature , date, age deviation from mean etc
4. Ratio scale: is an interval scale with the additional feature
of an absolute zero point. With a ratio scale, ratios of numbers do reflect
ratios of magnitude. Eg. weight. Height
NB: Quantitative/qualitative data
DATA ANALYSIS
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After the fieldwork has been completed, the data must be converted into a format that will answer the research questions.
The application of reasoning to understand the data that have been collected is known as data analysis
The raw data are often not in a form that can be
directly used for analysis.
There is, therefore, the need to process or prepare the data prior to the analysis.
Data preparation includes editing, coding, and data entry.
These activities ensure the accuracy of the data and their conversion from raw form to reduced and classified forms that are more appropriate for analysis.
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Raw Data
Coding
Editing
Data File
Analysis Approach?
Univariate Analysis
Descriptive Analysis
Bivariate Analysis
Multivariate Analysis
Figure 1.1: Overview of the Stages of Data Analysis
Error checking
takes place in each of
these stages
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STAGES OF DATA ANALYSIS
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1. EDITING
Editing is the process of checking the completeness, consistency, and legibility of data and making the data ready for coding and transfer to storage.
Editing detects errors and omissions on questionnaires or other data collection forms, corrects them when possible, and certifies that maximum data quality standards are achieved.
When a problem or an error is detected in the process, the editor has to adjust the data to make them more complete, consistent, or readable.
In some instances, the editor may need to reconstruct data especially when the probable true response is very obvious.
Specifically, editing guarantees that data are:
Accurate.
Consistent with the intent of the question and other
information in the survey.
Uniformly entered.
Complete.
Arranged to simplify coding and tabulation
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A daily field edit enables enumerators to identify respondents who should be recontacted to fill in omissions in a timely fashion.
The supervisor may also use field edits to spot the need
for further interviewer training or to correct faulty
procedures.
Central (In-house) Editing
A rigorous editing by a single editor in a small study or by a team of editors in the case of a large inquiry performed at a centralized office.
Central editing takes place when all forms or schedules have been completed and returned to the office.
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The editor must analyze the instruments used by each interviewer to detect falsification of data and obvious errors such as an entry of data in the wrong place, specifying time in days when it was requested in weeks etc.
When answers provided are out of range of expected values or not related to the question asked or missing, the editor can sometimes determine the proper answer by reviewing the other information in the data set.
If the correct answer cannot be easily determined based on the other information available on the respondent, the editor can strike out the answer (and replace it with “no answer” or “unknown”) if it is deemed inappropriate.
In some instances, the respondents can be contacted for clarification
Useful Rules to Guide Editors
Be familiar with instructions given to interviewers and coders.
Do not erase, or make illegible the original entry by the interviewer or respondent; original entries should remain legible.
Make all editing entries on an instrument or in a data set in some distinctive colour and in a standardized form.
Initial all answers changed or supplied.
Place initials and date of editing on each instrument completed or in a separate field within a data set.
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2. Coding
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The process of assigning a numerical score or other character symbol to previously edited data (or answers) so that the responses can be grouped into a limited number of categories.
Assigning numerical symbols permits the transfer of data
from questionnaires or interview forms to a computer.
Codes can be broadly defined as rules for interpreting, classifying, and recording data in the coding process; also, the actual numerical or other character symbols assigned to raw data.
In coding, categories are the partitions of a data set of a given variable
For instance, if the variable is gender, the partitions are male and female
Both closed- and open-response questions must be coded prior to data analyses
Basic Rules for Code Construction
There exist two basic rules for code construction
i. The coding categories should be exhaustive, meaning that a coding category should exist for all possible responses.
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ii. The coding categories should be mutually exclusive and independent. This implies that there should be no overlap among the categories to ensure that a subject or response can be placed in only one category.
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iii. The categories should be appropriate to the research problem and purpose.
iii. The categories within a single variable should be
derived from one classification dimension. This means every option in the category set is defined in terms of one concept or construct.
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Data Entry The process of transferring (coded) data from a research project,
such as answers to a survey questionnaire, to computers for viewing and manipulation.
Keyboarding remains a mainstay for researchers who need to create a
data file immediately and store it in a minimal space on a variety of
media.
However, an optical scanning system may be used to read material
directly into the computer‟s memory.
Voice recognition systems are alternatives for the telephone
interviewer.
Data verification or cleaning is necessary to ensure that all codes are legitimate
Descriptive Analysis
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The elementary transformation of raw data in a way that describes the basic characteristics such as central tendency, variability and shape of the distribution .
Central Tendency
A statistical measure to determine a single score that defines the centre of the distribution. The goal is to find the single score that is most representative of the entire group.
Mean
Median
Mode
Spread (variability)
A measure how the individual distributions are deviated from the averages like mean, median or mode.
Variance;
Standard Deviation
and
Range ; (R = Xmax – Xmin)
Interquartile Range ; Q3 – Q1 where N = Total frequency
• For example. Find the interquartile range given the data 3, 4, 5, 7, 9, 10, 11, 13
1 𝑄1 =
4 𝑁
3 𝑄3 =
4 𝑁
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Symmetric Distribution: The right hand side of the distribution is a mirror image of the left hand side.
Positively skewed scores pile up on left tapers off on the right
Negatively skewed scores pile up on the right tapers off on the left
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Shape/Distribution
Nominal and ordinal data are often described using frequency tables, percentages and graphs (e.g. bar chart)/charts (i.e. pie chart)
To obtain descriptive statistics (using SPSS)
1. Click on Analyze >> Descriptive Statistics >> Explore to obtain
the Explore dialogue box.
2. Transfer to the Dependent List box by clicking and
highlighting those variables for which you wish to obtain
descriptive statistics.
3. In the Display box click on Statistics which will bring up
the Explore: Statistics dialogue box.
4. Ensure Descriptive is chosen. Select Continue >> OK to
produce the output
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Tabulation
The orderly arrangement of data in a table or other summary format
showing the number of responses to each response category; tallying.
Frequency table: A table showing the different ways respondents
answered a question.
Cross-tabulation/ Contingency table : A data matrix that displays the
frequency of some combination of possible responses to multiple
variables; cross-tabulation results
• Cross-tabs allow the inspection and comparison of differences among
groups based on nominal or ordinal categories
To obtain a cross-tabulation
• Click on Analyze >> Descriptive Statistics >>Crosstabs …
• This brings up the cross-tabulation dialogue box.
• Two variables are transferred to row(s) and the other to column(s) box respectively.
• Click on OK to obtain the output.
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Graphs and Charts for Displaying Descriptive Statistics Frequency polygon: The most common ways of representing frequency
distributions graphically are by numerous variations of the frequency polygon, the simplest of which is the line graph
1. Click Graph >> Line.
2. In the Line Charts dialogue box select Simple.
3. Choose Summaries for Groups of cases.
4. Click Define to produce the Define Simple Line
5. Summaries of Groups of Cases: dialogue box.
6. Select the variable you wish to plot and then click the arrow button to place it into the Category Axis box.
7. Select OK.
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Bar charts
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A common method of presenting categorical data is the bar chart where the height or length of each bar is proportional to the size of the corresponding number.
1. Click on Graphs >>Bar … on the drop down menu.
2. The Bar Chart dialogue box provides for choice among a number of different bar chart forms.
3. The Define Simple Bar dialogue box
emerges with a variety of options for the display. We have
chosen N of cases but there are other options for you to explore
4. Transfer the required variable
5. Click OK and the output presents the Bar Chart
Box Plot
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• The box plot is useful for detecting skewness of distributions by noticing where the median is located and disparities between the lengths of the two whiskers.
• In a symmetrical distribution, the median is centred and the whiskers are of equal length.
Click on Graphs >>Ligacy Dialogs … On
the drop down menu select boxplot
The Boxplot Chart dialogue box provides for choice among simple and clustred boxplots as well as summaries for group cases and summaries for separate variables.
For simple boxplot, select simple and summaries for separate variables.
Transfer the required variables to the boxes represent
space Click OK and the output presents the Boxplot
Research Writings
Dr. Emmanuel Kwesi Arthur
© February 2020
Parts of a Manuscript
Title
Abstract
Introduction
Methods
Results
Discussion
Acknowledgements
References
Title, key words and abstracts are used for electronic searches
Title- The Backbone of an Article
It indicates content and main discoveries and attracts the readers attention.
It decides whether article is worth reading or will get attention of the readers.
Go for the Journal instruction in writing titles.
Examples:
Good Title: The Natural Product Cyclomarin Kills Mycobacterium Tuberculosis by Targeting the ClpC1 Subunit of the Caseinolytic Protease
(online article in Angewandte Chemie International, 11 May 2011)
Bad Title: Anti-Tuberculosis agent Cyclomarin.
Attractive and Catchy Title – makes reader going through the article for sure
Graphics plays an important role in catching the eyes of readers.
Nature’s style -Manuscript Formatting Guide
Titles
Titles do not exceed two lines in print.
Titles do not normally include numbers, acronyms, abbreviations or punctuation.
They should include sufficient detail for indexing purposes but be general enough for readers outside the field to appreciate what the paper is about.
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Should be informative, indicative and reflects the main „story‟ of the article.
The only chance you have to get the reader‟s attention.
Should be crisp, concise and accurate.
Gives the quick idea of the contents (Stand alone).
What and how was done
Provide a brief conclusions
I generally write abstract at the end
The detailed information must be present in the body text, not in abstract.
Abstract- Most Critical Part of Paper
Structured IMRaD formula (will discuss more on
next slide)
Unstructured Paragraphs- few sentences
summarizing each section
Skeleton of an Article
Introduction--- What is the? Materials and methods/experimental procedures-- What did you do? Results-- What did you find? and Discussion-- What does it mean?
Skeleton of an Article-Continued IMRaD structure- Writing a
draft
Huth EJ. Writing and Publishing in Medicine, 3rd ed. Baltimore: Williams & Wilkins; 1999.
Scientific Writing: My Approach and Irreverent Opinions, Mark Yeager.
< 2% readers actually cite your article
And among these < 2% approximately 98% reader just read the introduction
Brief background information of the current study
Focused
Integrated review of pertinent work
Updated literature citation
Should not be too long
Importance of current study/advancement needed/summary of new findings
Introduction- Setting the Scene
Ask question to yourself that why should anyone read your paper amongst the 1000‟s appearing that month?
Create-A-Research-Space
It should introduce the topic and relates to the existing research.
significance of your research.
Capture your audience. Why is your experiment important?
Avoid comprehensive review, self citations, etc
Introduction
Material and Methods Write the methods section first because it is the easiest to
write.
Provide enough details for competent researchers to repeat the experiment (Who, What, When, Where, How, and Why?)
Start writing when experiments still in progress
Sufficient information must be provided for reproducibility
Study design-new methods must be described in detail
Supplies, manufacturer, country needs to be added
Animal, human, protections details
Measurements/ instruments
Statistical analysis and data collection
Descriptive subheadings– general experimental methods, animals, spectral data, etc
Use descriptive headings that concisely state the results.
Data representation-concise and accurate.
Short and easy to understand
Consistent with the abstract and introduction
Give tables and figures where needed
With sufficient information so that minimum text is required.
Don‟t repeat information in graphics and text.
Results
Appropriate numbering of figures and table mentioned in the text.
Use significant figures where required.
Avoid speculations and over discussion.
Avoid using words such as proves, confirmed, removed all doubts, etc. Remember science is dynamic and ever changing.
Results
Discussion
Hardest section to write, but it is also the most important.
Use descriptive headings that concisely summarize the interpretation of the results.
Answer the question posed in introduction
Correlation of your finding with the existing knowledge
Discrepancies between new results and previously reported results.
Discussion
What is new without exaggerating.
Conclusion/summary, perspectives, implications.
Research limitations and need for future research.
Theoretical implications and possible practical applications.
Identify key findings and application
Should not be a summary of the work done-
abstract is doing fine with that.
Consistent with experimental and introduction
Conclusion
References
Cite current and key pertinent references
Reference citations must be accurate and complete
Read the references
Use correct style for journal
Acknowledgments
Funding agencies
Intellectual contributions
Dedications
Notes
Process of Research and its Publication
Completion of research
Preparation of manuscript
Submission of manuscript
Assignment and peer review
Decision
Revision
Resubmission
Re-review
Acceptance
Publication
Rejection
Rejection
The most important factors that influence whether your manuscript will be considered/reviewed for publication
are the title, abstract, cover letter, and your reputation based on your
previous work.
Do’s and Don’t in Scientific Writings
Be factual Be honourable Be legal Be truthful Be objectives Be accurate
Don‟t deceive Don‟t falsify Don‟t plagiarize
Do you agree with the authors‟ rationale for setting up the experiments as they did?
Did they perform the experiments appropriately?
Were there enough experiments to support the major finding?
Do you see trends/patterns in their data?
Do you agree with the author‟s conclusions?
What further questions do you have?
What might you suggest they do next?
Reflection and Criticism
Thesis Write Up
Outline What is thesis? Structure of a thesis Title page Declaration Acknowledgement Abstract Chapters Referencing
What is thesis?
A long essay or dissertation involving personal research,
written by a candidate for a university degree
A thesis or dissertation is a document submitted in support of
Candidature for an academic degree or professional qualification
presenting the author’s research and findings
Structure of a thesis Thesis is structured to have
Title page
Declaration
Acknowledgement
Abstract
Chapters
Referencing
Title page
What goes into the title page?
this page is not numbered.
The title:
10-15 words is most common.
Must be sufficiently specific.
Declaration
Author declares the validity of the work by declaring its conformity to standards.
Authors also declares that ideas, assertions and opinions of other researchers used in the work has been duly referenced.
Acknowledgement
Author shows appreciation to
individuals
corporations
institutions as well as
supervisors
Abstract Abstract is concise summary of a project thesis.
Abstract contains
I. Objectives II. methodology III. results and discussion IV. conclusions
A well written abstract should be understandable to
any reader and concise.
Copyright: David Thiel 2009
The Abstract – a general guide
2 sentences on the wider field – context and
significance.
2 sentences on the research method
2 sentences on the results and conclusions.
Chapters
The chapters of a thesis include:
Chapter 1- introduction
Chapter 2- literature review
Chapter 3- methodology
Chapter 4- Results and discussion
Chapter 5- conclusion and recommendations
Chapter 1- introduction This chapter is also is sub divided into sections.
These sections are:
1. Background of study
2. problem statement
3. Aims and Objectives
4. Scope of study
5. Significance of study
1.Background of Study
Background of study should contain
1. brief history of the problem.
2. summarised reviews of pertinent works
3. Proposed solution or aim of current work.
Referencing of information is indispensable.
2. problem statement
Describe the „‟ideal‟‟ state
of affair
Explain your problem
Explain the problem‟s financial costs
[why it‟s a big deal]
Back your assertion
Propose a solution
Explain the benefit of the solution
Conclude by summarizing the problem
and solution
A problem well-stated is a problem half solved
3. Aims and Objectives what are the expectations that the author wants to meet at the end of the project?
4. Scope of Study
Describes the extend of study
Provides limitation [influences that the researcher cannot control] for study stretch
Narrows the research coverage of project
divisions
5. Justification
Discusses the reasons in conducting the research
Possible solutions to problem
Significance of study
Chapter 2- literature review
Copyright: David Thiel 2009
Literature Review
Who has done what and how?
What is their plan for “further work”?
Have they reported more recent work in a conference?
What opportunities are available for confirming the results of others and expanding their results and conclusions?
Chapter 3- methodology
In this chapter the author 1. discloses how, when and where raw materials were obtained.
2. gives a detailed description of materials preparation.
3. discloses facilities as well as equipment used.
4. various tests that were carried out.
5.discloses data collection methods and data analysing tools.
Chapter 4- Results and discussion
Results
What was the Out come?
Chapter 4- Results and discussion
Discussion
This the art of interpreting or explaining the meaning of results in a thesis.
It involves
I. A direct, declarative, and succinct presentation of the results.
II. Explaining the findings and their implications.
III. Explanations which do not favour your arguments must not be ignored.
IV. Identification of all limitations in the work.
Chapter 5- conclusion In this chapter, the author must
Must implicitly restate the thesis position
Emphasize the importance of the project
Offer suggestions for the future based on what has been argued
End on a relevant and powerful quote.
And the CONCLUSION!
The concluding paragraph (5-8 sentences) should include the following:
1. Restate the problem statement.
2. Restate the hypothesis.
3. Accept or reject the hypothesis using the analysis of your data. Be specific, proving your point with specific data points and trends.
4. Include a discussion of the validity of your results.
5. How might this experiment be improved or modified to further test the problem statement.
6. Summarize or restate you conclusion to finish up!
***This must be written in the third person!***
Referencing
Limitation of Research
Limitations are potential weaknesses in your study and are out of your control.
We find limitations in almost everything we do.
Example of limitation is time. A study conducted over a certain interval of time is a snapshot dependent on conditions occurring during that time.
You must explain how you intend to deal with the limitations you are aware of so as not to affect the outcome of the study.
Delimitation of Research The delimitations are those characteristics that limit
the scope and define the boundaries of your study.
The delimitations are in your control.
Delimiting factors include the choice of objectives, the research questions, variables of interest, theoretical perspectives that you adopted (as opposed to what could have been adopted), and the population you choose to investigate.
Your first delimitation was the choice of problem itself; implying there are other related problems that could have been chosen but were rejected or screened off from view.
Delimitation of Research
Your purpose statement explains the intent that clearly sets out the intended accomplishments, and also includes and implicit or explicit understanding of what the study will not cover.
Assignment 3
1. Identify the research problem.
2. Identify the research plan.
3. How did they collect the data?
What equipment/methods/procedures did they use?
4. How did they analyze the data?
5. Did they formulate hypotheses? If yes state the hypothesis and if No formulate your own hypotheses and how to test them.
Bring one copy of a full-text article published recently on a topic of your interest that is related to Materials Science and Engineering.
Assignment 3 Cont’d
6. What were the conclusions? Future studies?
7. Identify the purpose statement.
Additional Assignment 3
1. Re-write the title using 5 – 8 words.
2. Re-write the title using 15 – 18 words.
3. Provide the delimitations for this study.
4. What are 2 examples of the limitations of this study?
5. Does this study answer the research questions?
Assignment 3 Bring copies (for everyone, 48total) of a full-text article
published recently on a topic of your interest that is related to Environmental Resources Management.
Provide a written summary (1-2 pages, double spaced, times roman font) of your answers and answer the following questions.
You‟ll be asked to give a brief oral presentation (5 – 7 min) regarding your article and your answers to the following questions:
1. What is the research problem? 2. What is the purpose statement? 3. What were the delimitations of this study? 4. What were some potential limitations of this study? 5. What were the initial hypotheses for this study? 6. Where the hypotheses rejected or accepted? 7. What was the overall conclusion of this paper? 8. If you were to replicate this study, describe how you would do it at
KNUST.
Warm-up Questions Vitamin C Lab!!!
Background information:
Today, we are analyzing sources of vitamins and minerals in our diets. We will investigate which source of orange juice would have the greatest amount of Vitamin C. (Here: Fresh Squeezed, Bottled 100% juice, and mix from frozen concentrate)
Research indicates that as long as vitamin C is present, the juice will remain orange when iodine and cornstarch are added. As soon as the vitamin C is gone, the iodine will react with cornstarch to change the mixture to dark gray or brown.
Using the following parameters:
Test 20 ml of each juice combined with 0.5 g of cornstarch
Think about the indication of reaction you are looking for…how will you measure or compare this between samples?
NOW - Using what you know about the scientific method, complete the following:
Problem:
Hypothesis:
Independent Variable:
Dependent Variable:
189 2/1/2020
190
Take Home Exams 1. Select a topic guided by experimental perspective and
curiosity. Frequently guided by the source of funding for the research.
2. Define the problem in considerable detail, specifying exactly what you want to learn.
3. Review the literature to use what is already known about the topic. As a guide, and to generate ideas as to what questions to ask.
4. Formulate your hypothesis, describing how you expect your variables to be related. Your variables need to be operationalized.
5. Choose a research method, which we have discussed. 6. Discuss how you will collect your data paying attention to the
validity. 7. How will you analyze your data. 8. Discuss how you will disseminate your findings.
Writing a Student
Research Proposal
Proposal Requirements
Limit = Face page + six single spaced pages
Signed Face Page
Aims, Objectives & Significance (1/2 page +)
Background & Rationale (2 pages)
Materials & Methods (3 pages)
Future Directions (a paragraph)
References
Budget (if supplies, expenses needed )
Acknowledgement
Some of the ideas and concepts were adapted from “Writing Winning Grants” developed by Stephen W. Russell and David C. Morrison, Grant Writers‟ Seminars and Workshops, LLC.
More information at: http://www.grantcentral.com
Writing A Proposal
Preliminaries
Talk to your mentor – have regular meetings
Develop a project that you will complete
Pick a project that is worthwhile
Review the literature
Something that really contributes to science is most likely to be funded
Pick a project that is feasible (i.e., ~6-8 weeks), but not too “easy”.
Review of Proposals
No one will read all of the proposals carefully (too time-consuming)
Limited expertise of reviewers – they may not be familiar with your line of research
That is, don’t assume your reviewers know much about your topic
Review of Proposals So, the student/mentor must gain the genuine
confidence and enthusiasm of the assigned
reviewers
The student/mentor must be sure that the
reviewers also understand the science and the
importance of the research AND…..
Impress committee members not assigned to
review their proposal
Thus, one has to sell their idea to the reviewers
and educate them!
Writing the Proposal
To maximize effectiveness, it is essential to spend the most time working on the portions of the grant that reviewers read first, and all reviewers are likely to read…..
The Aims, Objectives & Significance Section
Specific Aims/Hypotheses
Begin writing these first, and take time to refine them
Be very careful with wording
Should set the stage for the rest of your proposal and gain the attention of the reviewers
A “blueprint” for your project
Aims, Objectives & Signficance Section
Suggested Elements:
Introductory Paragraph – broad (public health) significance of the research
Long-term research goal (of this line of research)
Overall objective/hypothesis of this project
Rationale (brief)
Specific Aims/Objectives or Hypotheses to be tested
Expected outcomes & future opportunities
Specific Aims/Hypotheses
• While the prevalence of dental caries has declined for the majority of U.S. children in recent decades, there are profound disparities in dental caries experience where children from low-income or minority families suffer a disproportionate share of the disease burden. ….
• The rationale for this study is that …
• Thus, the goals for the proposed study are to ….
• We plan to accomplish our objectives by addressing the following specific
aims:
1. To determine the prevalence of cavitated and non-cavitated carious lesions as well as visible plaque in a sample of 1-year-old children enrolled in southeastern Iowa WIC programs.
2. To determine the prevalence of Streptococcus mutans (SM) carriage and salivary SM
• levels in children and their mothers among southeastern Iowa WIC-enrollees.
• The results will be significant because……
Specific Aims/Hypotheses
Brief and specific
Generally, not too many – no more than 2-3 aims (and maybe only 1)
Carefully worded
In order, but should not be dependent on preceding aim(s)
May be helpful to have a working hypothesis for each aim
Specific Aims/Hypotheses
An example:
Specific Aim:
To compare micro-tensile bond strength obtained by using two different adhesive systems – A & B
Hypothesis:
Our hypothesis is that system A, which relies on displacing water with ethanol, will produce stronger short- and long-term bond strengths than system B.
Background & Rationale
Literature Review (Background)
Not meant to be exhaustive – just enough so you can demonstrate that you know what you‟re talking about and enough to support your research
Meant to provide background for your research Be sure references are up-to-date
Rationale
How does your research fill a gap in or contribute to the literature?
Why is it important?
Methods
Describe what will be done – how data will be acquired and what materials to be used
How many subjects/samples to be included & why this number was chosen
Describe any measurements to be made:
Instruments used
Who is doing the measuring
Training (if student to do measurements)
Very Important – Make sure student’s role is clearly described
Methods Helpful to have summary description of overall
protocol – A list of steps, a flow chart or diagram may also be helpful
Should have a timeline
Include data management and analyses plan
Statistical tests
Power calculations (i.e., justification for sample size)
Ideally, work with statistician in advance
Again, be sure to make clear what your (the student‟s) role will be in the project – specific tasks
Future Directions
Describe what this research will lead to for you in future years, or how it will help your mentor develop further research – what‟s the next step??
What related projects/area of research could possibly stem from the proposed project?
This section can be very brief – a couple of sentences
Bibliography & Budget
No more than about ½ page each
Bibliography should reflect relatively brief Background section – use a standard reference format as found in a scientific journal
Budget limited to about $250 for supplies, expenses, such as chemicals, reagents, specimens, expendable lab supplies. Also can include things such as copy costs, postage necessary for project. Poster costs OK, too.
Itemize and justify expenses
Other Issues
Be kind to your reviewers – use reasonable type size
and margins; shouldn‟t have to squeeze everything in
to meet page limits
Appendices are allowable, but not to circumvent page
limits
After submission, you will need to arrange a meeting
or meetings with one of your reviewers, you and your
mentor
We‟ll send out available times that reviewers have set aside for meetings
http://www.dentistry.uiowa.edu/student-research-proposals
