Sampling Basics II Research Aptitude By Talvir Singh

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• SAMPLE- represents the entire population.
• SAMPLING - Process of selecting a sample.
• SAMPLE' S feature/ mean - statistics.
• POPULATION 'S Feature/ mean - Parameter.
• LARGE SAMPLE - more than 30.
• Small sample - less than 30.
• Sample size & error--
1. large sample size ~ less error chances.
2. Small sample size ~ more error chances .
• Types of sampling --
1. PROBABILITY SAMPLING -aka-( Random sampling)
a) simple random sampling - random selection of sample. Each unit have equal probability of selecting as a sample.
b). Systematic sampling -
First unit randomly selected, and then after a sequencial pattern follow. Example - first unit randomly selected 3, then after 3 next no. Would be 6,9,12,18.etc
c). Stratified sampling -
Homogenous within the group.
Heterogeneous between the group.
d) Cluster sampling -
Naturally formed group- selected as a sample.
•Heterogeneous within the group .
• Homogeneous - between the group.
2) NON PROBABILITY SAMPLING - aka (Non -random sampling).
Types-
1. Convenience sampling
( Key- Accessibility)
2. Snow ball sampling - aka chain/ network sampling.
3. Purposive sampling- aka judgemental sampling
Key - Based on purpose
4. Quota sampling
Key - on the basis quota pre - determined.
• PROBABILITY SAMPLING - used for Quantitative research.
• NON PROBABILITY SAMPLING - used for Qualitative research.
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