Download - Selection of a sample
Contents
SELECTION OF A SAMPLE
- The Simple Random Sample
- The Systematic Sample
- The Stratified Random Sample
- The Area or Cluster Sample
TYPES OF SAMPLE
- Probability sampling
- Non-probability sampling
PopulationIncluding all people or item with the characteristic one wishes
to understand.
Area where the results of the study are generalized.
Because there is very rarely enough time or money to gather
information from everyone or everything in a population,
the goal becomes finding a representative sample (or
subset) of that population.
Examples of Population
All students of class X in Rawalpindi district.
All seventh grade students of IMCBs.
All the foreign students enrolled in NUML.
…..
SAMPLE
- A smaller group, which is selected from the
population to be included in the research.
- Sample has to be representative of characteristics of
the population.
- Results are drawn from the sample and
generalized to the entire population.
- Sample size depends upon the requirements of the
research.
Sampling Design Process
Define Population
Determine Sampling Frame
Determine Sampling Procedure
Probability Sampling
Simple Random
Sampling
Stratified Sampling
Cluster Sampling
Non-Probability Sampling
Convenience
Purposive
Quota
Snow ball
Determine Appropriate
Sample Size
Execute Sampling
Design
Why Sampling?
Time saving
Cost saving
Examine in greater detail
More scientific
Representative
Accessible
….
Major Sampling Techniques
Two types of major sampling techniques
1. Probability sampling
2. Non-probability sampling
Probability Sampling
Every individual in the population has greater than zerochance of selection.
Ensures a more representative sample
Types of probability sampling
1. Simple random sampling
2.Stratified sampling
3. Cluster sampling
Simple Random Sampling
Define population
Develop sampling
frame
Assign each unit a
number
Randomly select the required
amount of random
numbers
Systematically select random numbers until it meets the sample size
requirements
Every member of population
has equal probability of selection.
Used in case of homogeneous population
Use any of the techniques for random
selection such as draw, use of random number table
Stratified Sampling
Where population embraces a number of distinct
categories, the frame can be organized into separate
"strata." Each stratum is then sampled as an independent
sub-population, out of which individual elements can be
randomly selected. Every unit in a stratum has same chance
of being selected.
Using same sampling fraction for all strata ensures
proportionate representation in the sample.
Adequate representation of minority subgroups of interest
can be ensured by stratification & varying sampling
fraction between strata as required.
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Stratified Random Sampling
-Used in case of heterogeneous population
-Population split up into different strata on the bases of theirpeculiar features of interest to researcher.
-Then random sample picked proportionately from eachstratum. e,g gender, age, ethnic group etc
Cluster Sampling
Selecting a sample based on specific, naturally occurring
groups (clusters) within a population.
Example: randomly selecting 10 public sector universities
from a list of all public sector universities in Pakistan.
Systematic Sampling
List the population with serial numbers.
-Determine the sample size.
-Divide the population by SS to find out Kth case.
-Randomly start taking every kth case.
-Go on picking every kth case.
-Continue even afresh till you complete the sample size.
Non-Probability Sampling
- Where in every member doesn’t have equal chanceof selection.
1. Purposive Sampling
Look for the population of your interest e.g. inselecting a school to perform experiment inmethods of teaching.
2. Quota Sampling
Just as in case of SRS, except that you purposefullyselect certain cases/units to give representation tocover the quota.
3. Snowball Sampling
Ask the sample to identify another one and go on tillthe completion of sample size.