Chapter 2: Collection of Data
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Transcript of Chapter 2: Collection of Data
COLLECTION OF DATA
A process of obtaining
numerical
measurements
process of gathering and measuring
information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes
TWO SOURCES OF DATA
1. Documentary Sources
Published or unpublished
reports, statistics, Internet,
letters, magazines,
newspapers, diaries, etc
a. Primary Data
Data gathered are original
b. Secondary Data
Data is taken from an original source which is computed and compiled.
2. Field Sources
Individuals who have sufficient knowledge and experience regarding the study under investigation.
METHODS USED IN DATA
COLLECTION
1. The Direct Method
referred as interview method
face to face encounter
2. The Indirect Method
questionnaire methodquestionnaire-lists of questions
3. The Registration Method
utilizing the existing data/fact/info which is kept systemized by the office concerned
4. The Observation Method
used to collect data pertaining attitudes, behaviour, values, and cultural patterns of the samples under investigation
5. The Experiment Method
cause and effect relationship
used in making a scientific inquiry
PLANNING THE STUDY
1. Estimate the number of items in the population.
2. Assess resources such as time and money
3. Determine the sample size using the Slovin’s formula
n = N 1 + Ne2
see table 1: Sample size for a Specified Margin of Error on page 21
n = sample sizeN = population sizee = margin of error
4. Pick the sample by using the appropriate sampling technique.
5. Prepare the questions to be asked in the interview or in the questionnaire.
TYPES OF QUESTIONS
1. Structured Question
one way or few alternativesclear, simple, objective and easy to answer and tabulate
2. Open-ended Questions
can be answered in many ways-probing or questions w/c elicit reasons
FEATURES OF A GOOD
QUESTIONNAIRE
short and clearavoid leading questionsalways state the precise units
can be answered y checking slots or stating simple names or brands
arrangement of questions should e carefully planned
limit questions to essential information
Two Major Ways of Selecting Sample
Units from a Population
known as simple random sampling
picking things at random means picking things without bias or any predetermined choice
A. Probability Sampling
Ways of Drawing Sample Units at
Random
numbers assigned to each member of the population
1. Lottery Sampling
the selection of each member of the population is left adequately to chance, and every member of the population has an equal chance of being chosen
2. Table of Random Numbers
used when there are only few sample units to be selected
a. Direct Selection Method
Two Ways of Conducting the Remainder Method:
b. Remainder Method
1. When the number taken from the table of random numbers is subtracted from the upper limit within which this number falls, the remainder is the sample unit.
b. Remainder Method
2. When the upper limit of the set is subtracted from the number taken from the random tables and yields a number equal or less than N, the remainder is the sample unit.
b. Remainder Method
used when the population is too large to handle
B. Restricted Random Sampling
TYPES OF RESTRICTED RANDOM
SAMPLING
units are obtained by drawing every nth element of the population
1. Systematic Sampling
nth = Total no. of elements in the population Desired Sample Sizenth = N n
ex: population 50,000; sample size 100; margin of error 10%. Determine the nth term
nth = N n
= 50,000/100= 500
a. Stratified Sampling the population is divided into groups based on homogeneity
the distribution of units is proportional to the total number of units in each stratum
Types of Systematic Sampling
1) Identify N and its different strata
2) Divide the members of the population into percent shares
3) multiply each percent share by n sample units to get the actual number of sample units for each stratum
steps:
Example
population is 50,000sample units is 100margin of error is 10 %25,000 belong to high income group10,000 belong to middle income group15,000 belong to low income group
strata
STRATA NUMBER OF POPULATION
High-income group 25,000Middle-income group 10,000
Low-income group 15,000TOTAL 50,000
DISTRIBUTION OF POPULATION
STRATA NUMBER OF POPULATION
PERCENT SHARE(N/n)
High-income group
25,000/50,000
Middle-income group
10,000/50,000
Low-income group
15,000/50,000
TOTAL 50,000
PERCENT SHARE OF EACH STRATUM
0.5 or 50%
0.2 or 20%
0.3 or 30%
100%
STRATA Sample size times the percent share
Number of Sample Units
High-income group
100 x 0.5
Middle-income group
100 x 0.2
Low-income group
100 x 0.3
TOTAL
DISTRIBUTION OF SAMPLE UNITS
50
20
30
100
b. Cluster Sampling an area sample: geographical basis
districts or blocksheterogeneous groups
Types of Systematic Sampling
c. Multi-Stage Sampling uses several stages in getting the samples from the general population
useful in conducting a nationwide survey
Types of Systematic Sampling
not all members of the population are given equal chances: sample
non-probability samplingchooses its sampleused in market research or employment department
2. Non-Random Sampling
a. Purposive Sampling choosing samples based on a criteria and rules by the researcher
Types of Non-Random Sampling
b. Quota Sampling the researcher limits the number of his samples based on the required number of subject under investigation
Types of Non-Random Sampling
c. Convenience Sampling the researcher conducts a study at his convenient time, preferred place or venue
Types of Non-Random Sampling