METHODOLOGY
DATA COLLECTION - SAMPLING
METHODOLOGY
DATA COLLECTION - SAMPLING
⭐ POPULATION
⭐ SAMPLE
✅ A population doesn't always refer a to people. It also can refer to objects
✅ A population is the entire group that you want to dram conclusions about
✅ A subset of a specific population
✅ The size of sample is always less than the total size of the population
Purpose of Sampling in Quantitative Design
🖊 To collect a lot of information from just few people
Example : ethnographic interview
Purpose of Sampling In Qualitative Design
🖊 Make sampling choices that enable them to deepen understanding of whatever phenomenon it is that they are studying
Two Stages Selecting Sample
Major Types of Sampling Techniques
1. Probability Sampling
🚩 Every member of the target population has a known chance of being included in the sample
2. Non Probability Sampling
🚩 The sample is selected based on non-random criteria, and not every member of the population has a chance of being included.
Types of Simple (ST) Random Sampling
1. Simple Random Sampling
🚩 Every member of the population has an equal chance of being selected
🖊 Multi Stage Sampling
2. Stratified Sampling
🚩 Involves dividing the population into subpopulations that may differ in important ways
🚩 Allows you draw more precise conclusions by ensuring that every subgroup is properly represented in the sample.
3. Systematic Sampling
🚩 Similar to simple random sampling, but it is usually slightly easier to conduct.
🚩 Every member of the population is listed with a number, but individuals are chosen at regular intervals.
4. Cluster Sampling
🚩 Involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample.
🚩 Randomly select entire subgroups
Non Probability Sampling Techniques
🚩 The term " sample " is perhaps less appropriate
🚩 Focus more upon a sample who can describe,explain and illuminate the phenomenon being explored
Two Types of Nones Probability Sampling
1. Haphazard/Convenience Sampling
🚩 A sampling method that does not follow any systematic way of selecting participants
Problem ❗ : No evidence that they are representative of the populations we're interested in generalizing
2. Purposive Sampling
( Main Category )
🚩 Known as judmental/selective sampling
Advantage :
✅ Easy to do research
✅ Cost is low and can collect data quickly
🚩 Sample with a purpose in mind
🚩 Very useful when you need to reach a targeted sample quickly
Sub Category
( Quota Sampling )
🚩 Select people non randomly according to some fixed quota
🖊 Proportional Quota Sampling
🚩 Represent the major characteristics of the population by sampling a proportional amount of each specific characteristics
Example : race,age
🖊 Non Proportional Sampling
🚩 Is a bit less restrictive
🚩 Typically use in assuring that small groups of samples are adequately represented
🖊 Snowball Sampling
🚩 Where research participants recruit other participants for a test or study
🚩 Useful when you're trying to reach population that are inaccessible or hard to find
🖊 Determining Sample Size
Notes ✏ : *Sample size relates to how many people/units to pick for study
*To generalize or show representiveness the size of the sample becomes an issue
🚩 Balance the need for as large as sample size with constraints based upon the issues of cost & time required for the analysis
🚩 Minimum sample size of 30 would normally be required
🚩 For small population, a sample of 50 should be a target
Common Error in Determining Sample Size
Error 1
❌ To assume the sample should be a certain percentage of the population
Error 2
❌ To assume that the finding from your sample will also be the true figure for the overall population
Evaluating Samples
Response rates : describes the extent to which the final data set includes all sample members
Sampling Error
🚩 The error which is made in selecting samples that are not represntatives of the population
🚩 Example of error
❌ Poor sampling design
❌ Inaccurate reporting by respondents
❌ Item not clear
Non Sampling Error
✅ Everything else beside sampling error
Qualitatives Sampling
BIAS - A major issue in the data gathering process
🚩 Saturation point
🚩 Identify the criteria that could be used to inform the sample
Types of Bias
i. Interviewer Bias
🚩 A distortion of response related to the person questioning informants in research
ii. Auspices Bias
🚩 The tendency to indicate your response because of the organization conducting the study
iii. Social Desirability
🚩 Type of response bias that is the tendency of survey respondents to answer question in a manner that will be viewed favorably by others
🚩 We use variety of ways in a research either one or two or combination of the random sampling techniques to help us more effective & efficient manner posibble
Name : Deana Dindat Ak Sulie ( 69482 )