Data Gathering, Sampling, Data Management And Data Integrity
Villanueva, Ryan Cloyd Q.
BA-Political Science 4
DATA GATHERING
Data are collection of numbers, quantities, facts, or records used as bases for drawing conclusions or making inferences. Data are what the researcher is searching for and which are subjected to analysis using statistical procedures, and interpretations, so that the interferences, principles of generalization are drawn.
Basic Steps:Administering the research instrument. If you are using a questionnaire, describe how you are going to proceed.
Recording Observations. Additional data may be collected through systematic recording of observations. It could also aid in a more accurate and interesting interpretation of data.
Use of Records and Documentation. Records and documents are very important sources of additional information.
Sources of Data
Primary Data. Primary data are those gathered from primary sources. The primary sources are as follows:
• Individual Persons•Organized Group or Organization such as fraternities, associations, schools, community, etc.• Established practices such as marriage, religious rites, legal system, and economic system.
Secondary Data are those gathered from secondary sources. The secondary resources are as follows:
• Books including dictionaries, encyclopedia, almanac, etc.• Articles published in professional journals, magazines, newspapers and other publications.•Unpublished thesis and dissertation and other studies.•Monographs and manuscripts.• All other second hand sources (verbal or written)
Research Instrument
Observation involves the researcher watching the research situation.
Interview is feasible when a personal interaction is available.
Questionnaire is a set of questions, arranged in sequence and designed to be self-administered.
SAMPLING METHODAccording to Amante, sampling means selecting a given number of persons, objects or events called subset from a given population by specified selection process. Sampling also refers to strategies of picking up a subgroup from a larger group to be used as a basis for making judgements about the larger group. The sub-group is the sample while the larger group is the population.
Importance of Sampling
The extent to which generalizations can be made from the results of a research depends much on the sampling techniques used and how appropriate it is. If the research findings are not generalizable to some degree beyond the sample used in the study, then the research cannot provide new knowledge, cannot advance education as a science and is largely a waste of time. Sampling should be carefully designed for satisfactory.
General Types Of Sampling
Probability Sampling – the sample is a portion (a certain percent) of the population and such sample is selected from the population by means of some way in which every element of the population has a chance of being included in the sample.
Non-probability Sampling – the sample is not a proportion of the population and there is no system in selecting the sample. The selection depends upon the population.
Types of Probability Sampling
Pure Random Sampling – this type is one in which everyone in the population of the inquiry has an equal chance of being selected to be included in the sample.
Systematic Sampling – this is the technique of sampling in which every nth name is a list may be selected to be included in a sample.
Stratified Random Sampling – is the process of selecting randomly samples from the different strata of the population used in the study.
Purposive Sampling – is determining the target population those to be included in the study.
Cluster Sampling – or multistage sampling is used when the population is too big or the geographical area of the research is large.
Types of Non-probability Sampling
Accidental Sampling – there is no system of selection but only those whom the researcher or interviewer meet by chance are included in the study.
Quota Sampling – specified numbers of persons of certain types are in the sample.
Convenience Sampling – it is a process of picking out people in the most convenient and to immediately get their reaction to a certain hot and controversial issue.
DATA MANAGEMENT• Category Response - the age and gender questions are examples of category response questions. •Quantity or Information Response - the questionnaire/s is encrypted with questions that aims to ask important information’s to the respondents of the study that could be useful on the further study of the research.• List Response - it may be that the respondent actually had multiple responsibilities and this would be particularly useful to know.
• Rating Scale Response - questions which ask respondents to rate their feelings or attitudes against a prepared scale are the mainstay of questionnaire design.• Ranking Response - these questions require respondents to rank a number of options in a particular order. •Open Response - open response questions are a must for questionnaire surveys if only as a ‘catch-all’ at the end to give respondents the opportunity to reveal any ideas/comments/ suggestions they have been harboring and not had the opportunity to articulate.
DATA ANALYSISCalculating FrequenciesThe frequency (f) of a particular observation is the number of times the observation occurs in the data. The distribution of a variable is the pattern of frequencies of the observation. Frequency distributions are portrayed as frequency tables, histograms, or polygons.Frequency distributions can show either the actual number of observations falling in each range or the percentage of observations. In the latter instance, the distribution is called a relative frequency distribution.
Thank You for
LISTening
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