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

  1. Define Population
  1. Determine Sampling Method

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

  1. Typical Quantitative Analysis

🚩 Balance the need for as large as sample size with constraints based upon the issues of cost & time required for the analysis

  1. Basic Descriptive Statistics

🚩 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

  1. Undercoverage
    🚩 Occurs when some parts of your research population are not adequately represented in your survey sample
  1. Nonresponse Bias
    🚩 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
  1. Response Bias
    🚩 The tendency of a person to answer questions on a survey untruthfully/misleading

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 )