1. July, 2014 HQ Sampling

2. AGENDA 1. A brief Overview of Sampling 2. Types of Random Sampling Simple Random and Systematic Random 3. Types of Probability Sampling Clustering Stratification 4. Multistage Complex Sampling 5. Practical example of Multistage sampling

3. Probability Sampling Methods Some Traits and When to use? When to use? When the population is definite and The results should represent the view of entire population. The Traits Random&Representative Chance for every element in the population to be selected The result is representative for the entire population We all have a chance to be selected! Hooray …

4. Random Sampling Methods Simple Random Sampling The “pick a name out of the hat” technique usually done by random number generator Systematic Random Sampling Every nth piece of data is chosen

5. Probability Sapling Methods Clustering Cluster sampling is a sampling technique used when "natural“ but relatively homogeneous groupings are evident in a statistical population and the cost of reaching every group is high.

6. Stratification When subpopulations within an overall population vary, the traits are different in each subpopulation, it is advantageous to sample each subpopulation (stratum) independently. Group agro Loan Group Business Loan Data is divided into subgroups (strata) based on specific characteristic Age Loan Type (size) Gender, etc. Assign your sample to the strata using proportional or optimal allocation Individual rural Loan Individual Business Loan

7. Stratification Proportional Allocation (use when your population is relatively homogeneous) The sample size of each stratum is proportionate to the population size of the stratum. Formula for Proportional Allocation n h = ( N h / N ) * n where n h is the sample size for stratum h, N h is the population size for stratum h, N is total population size, n is total sample size

8. Stratification Optimal Allocation (use when there is huge heterogeneity in your population) Larger variability larger should be samples from the stratum to generate the least possible sampling variance. Formula for Optimal Allocation n h = n * ( N h * σ h ) / [ Σ ( N i * σ i ) ] where n h is the sample size for stratum h, N h is the population size for stratum h, n is total sample size, σ h is the standard deviation of stratum h More variable more sample

9. Multistage Clustering Appling Clustering and Stratification to a Stat. Population

10. FCAT Sampling Practical Example On How to Sample