Sampling “Sampling is the process of choosing sample which is a group of people, items and objects. That are taken from population for measurement and population must be representative of population so that we can generalize our findings”

What is Population? “It is an accessible group of people who meets the eligibility criteria.” What is sample? “Subset of population selected for study.”

Concepts of sampling  Target population  Survey population  Element  Sampling unit  Sampling frame  Sample design

 Sample size  Sampling error  Margin of error  Confidence level  Statistical inference  Sampling bias

Types of sampling

Probability sampling 1. Simple random sampling Every person has a chance to be included in population Complete list of everyone Sampling frame

Simple random sampling

2: systematic random technique: Select the samples by following rules set by the researcher. We can select members if random start or starting point is determined. Example: Finding all kth samples.

3: stratified sampling Stratification is the process of dividing the members into homogeneous subgroups before sampling. Every element must be assigned to one stratum No element must be excluded.

4: cluster sampling Population is divided into groups rather than individuals. It is used for large scale survey. Make clusters and everyone in selected clusters is sample. 5: multi stage sampling Complex form of cluster sampling Design clusters Selecting what element within cluster to use.

Non-probability sampling Uses nonrandom procedures for selection Based on the judgment of researcher Biased Lack of objectivity Not reliable Economical

Types of non-probability sampling 1:Convenience sampling: Members are selected based on their availability and accessibility 2: Quota sampling : Nonrandom selection of members based on the identification of specific characteristics to increase the representativeness of sample. E.g. people aged 65 are interviewed.

3:judgmental sampling: People with specific characteristics are selected based on the judgment and knowledge of researcher about population Example: Want to know the opinion of drivers who got penalty points or who are disqualified as a result of speeding issues.

Sample size No of people that will be included in study. Before deciding sample size you must identify what you will include and exclude in study. Sample size depends on: 1. Type of data to be analyzed 2. Desired accuracy one wishes to achieve 3. No. of comparisons that will be made 4. No. of variables that will be examined

Selection of sample size Power of a test of hypothesis For this approach researcher must be clear that what he wants to know. For large projects we can hire the skills of statistician. For small scale projects computer software packages are available to determine sample size.

conclusion Probability sampling study findings that can generalize to population Non-probability sampling study findings that can be generalized to the institution or place where the sample was studied.