1. Sampling Sampling is a process of selecting a few(sample) from a bigger group(study population). Population is usually represented by N and number of selected sample is called sample size usually denoted by n. Way of selecting a sample from population is called sampling design. Two types – Probability, Non-probability Sampling

2. Probability sampling method In Probability sampling method selection criteria for the respondent from the population is on the basis of probability. Three types – 1.Simple random sampling 2.Stratified sampling 3.Cluster Sampling.

3. Simple Random sampling Every member has equal and independent chances of being selected. It requires complete list of elements and ID No to each. Can be done on the basis of Computer programming or draw system or on the basis of random number table.

4. Stratified Sampling Applicable/useful when population consist of a number of heterogeneous subpopulations. Populations is divided into subgroups/segments called strata. Basis can be location, age, industry, gross sales, number of employees. Within group- Homogeneous and inter group heterogeneous. Eg. Top Mgt, Middle Mgt, Lower management, Supervisor, sartorial staff. A simple random sample sample is drawn from each strata in proportion or non-proportion to its size.

5. Cluster Sampling Also known as Area Sampling Method. Population is divided in to smaller groups called clusters. Inside the clusters, elements also called as elementary units are as heterogeneous as population. Eg Committee from various departments for product development. Cluster sampling offer more heterogeneity within group and more homogeneity among groups reverse of stratified sampling. Cluster sampling invites preparing list of clusters instead of list of elements. Eg. List of residential colonies(Blocks), for door-to-door interviews.Airline select random set of flights for distribution of questionnaire on customer satisfaction applying cluster sampling.

6. Non-Random Sampling Do not follow theory of probability. Used when elements in population is unknown or can not be identified. Types – 4. 1.Convenient Sampling. 2.Purposive sampling. 3.Judgmental Sampling. 4.Quota Sampling.

7. 1.Convenient Sampling : Units are included depending upon convenience of a researcher. Eg. For project on food habits among adults- researcher may choose his/her friends as easily available. 2.Purposive Sampling. Specific target respondents who will be able to provide desired information or satisfy prescribed creteria. Eg. Frequency of visits, ussage, MBA students for B schools, or insurance providers.

8. 3. Judgmental Sampling. Researcher uses judgmental selection criteria. Test market & many product tests on selected shopping malls. Selection of one or few markets representative of population. 4.Quota Sampling Proportionate sampling for demographic characteristics w.r.t population. Quota is different then stratified on two ways- one in stratified it is random basis for selection whereas in quota non random basis, secondly in quota basis for grouping is demographics whereas in strata basis for grouping is research need based factors. Eg 10 male and 10 female (60% F with income more then 1lakh) (40% M income more then 1 lakh) Age 0-25 Yrs - 12% 25-50 Yrs- 63% 50+-25%

9. 3. Judgmental Sampling. Researcher uses judgmental selection criteria. Test market & many product tests on selected shopping malls. Selection of one or few markets representative of population. 4.Quota Sampling Proportionate sampling for demographic characteristics w.r.t population. Quota is different then stratified on two ways- one in stratified it is random basis for selection whereas in quota non random basis, secondly in quota basis for grouping is demographics whereas in strata basis for grouping is research need based factors. Eg 10 male and 10 female (60% F with income more then 1lakh) (40% M income more then 1 lakh) Age 0-25 Yrs - 12% 25-50 Yrs- 63% 50+-25%