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METHODOLOGY DATA COLLECTION - SAMPLING, Sub Category ( Quota Sampling…
METHODOLOGY
DATA COLLECTION - SAMPLING
:star: POPULATION
:check: A population doesn't always refer a to people. It also can refer to objects
:check: A population is the entire group that you want to dram conclusions about
:star: SAMPLE
:check: A subset of a specific population
:check: The size of sample is always less than the total size of the population
Purpose of Sampling in Quantitative Design
:pen: To collect a lot of information from just few people
Example : ethnographic interview
Purpose of Sampling In Qualitative Design
:pen: Make sampling choices that enable them to deepen understanding of whatever phenomenon it is that they are studying
Two Stages Selecting Sample
Define Population
Determine Sampling Method
Major Types of Sampling Techniques
1. Probability Sampling
:red_flag: Every member of the target population has a known chance of being included in the sample
2. Non Probability Sampling
:red_flag: 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
:red_flag: Every member of the population has an equal chance of being selected
2. Stratified Sampling
:red_flag: Involves dividing the population into subpopulations that may differ in important ways
:red_flag: Allows you draw more precise conclusions by ensuring that every subgroup is properly represented in the sample.
3. Systematic Sampling
:red_flag: Similar to simple random sampling, but it is usually slightly easier to conduct.
:red_flag: Every member of the population is listed with a number, but individuals are chosen at regular intervals.
4. Cluster Sampling
:red_flag: Involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample.
:red_flag: Randomly select entire subgroups
Non Probability Sampling Techniques
:red_flag: The term " sample " is perhaps less appropriate
:red_flag: 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
:red_flag: 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
Advantage :
:check: Easy to do research
:check: Cost is low and can collect data quickly
2. Purposive Sampling
( Main Category )
:red_flag: Known as judmental/selective sampling
:red_flag: Sample with a purpose in mind
:red_flag: Very useful when you need to reach a targeted sample quickly
:pen:
Determining Sample Size
Notes :pencil2: :
*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
Typical Quantitative Analysis
:red_flag: Balance the need for as large as sample size with constraints based upon the issues of cost & time required for the analysis
Basic Descriptive Statistics
:red_flag: Minimum sample size of 30 would normally be required
:red_flag: For small population, a sample of 50 should be a target
Common Error in Determining Sample Size
Error 1
:red_cross: To assume the sample should be a certain percentage of the population
Error 2
:red_cross: 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
:red_flag: The error which is made in selecting samples that are not represntatives of the population
:red_flag: Example of error
:red_cross: Poor sampling design
:red_cross: Inaccurate reporting by respondents
:red_cross: Item not clear
Non Sampling Error
:check: Everything else beside sampling error
Qualitatives Sampling
:red_flag: Saturation point
:red_flag: Identify the criteria that could be used to inform the sample
BIAS - A major issue in the data gathering process
Types of Bias
Undercoverage
:red_flag: Occurs when some parts of your research population are not adequately represented in your survey sample
Nonresponse Bias
:red_flag: Occurs when people are unwilling or unable to respond to a survey due to a factor that makes them differ greatly from people who respond
Response Bias
:red_flag: The tendency of a person to answer questions on a survey untruthfully/misleading
i. Interviewer Bias
:red_flag: A distortion of response related to the person questioning informants in research
ii. Auspices Bias
:red_flag: The tendency to indicate your response because of the organization conducting the study
iii. Social Desirability
:red_flag: Type of response bias that is the tendency of survey respondents to answer question in a manner that will be viewed favorably by others
Sub Category
( Quota Sampling )
:red_flag: Select people non randomly according to some fixed quota
:pen: Proportional Quota Sampling
:red_flag: Represent the major characteristics of the population by sampling a proportional amount of each specific characteristics
Example : race,age
:pen: Non Proportional Sampling
:red_flag: Is a bit less restrictive
:red_flag: Typically use in assuring that small groups of samples are adequately represented
:pen: Snowball Sampling
:red_flag: Where research participants recruit other participants for a test or study
:red_flag: Useful when you're trying to reach population that are inaccessible or hard to find
:pen: Multi Stage Sampling
:red_flag: 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 )