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Types of Sampling

Types of Sampling

neetagupta
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Types of Sampling

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  1. Sampling Techniques • Dr Neeta Gupta • Positive Psychologist • Associate Professor • Certified Practitioner of EFT & REBT (London) & CBT (Scotland) • DAV PG College • Dehradun Dr Neeta Gupta Positive Psychologist Associate Professor Certified Practitioner of EFT & REBT(London), CBT(Scotland) DAV PG College Dehradun

  2. Sampling Techniques Non-Probability Sampling Probability Sampling Purposive Stratified Random sampling Cluster Sampling Simple Random Sampling Quota Sampling Convenience Snowball Technique

  3. Probability Sampling: Probability sampling is one in which each and every member of the population has an equal chance of being selected .Randomization is the key for probability sampling and what is necessary is thateach individual must have a known probability of being included in the sample.

  4. Non-Probability Sampling: Non-probability sampling is one where there is no way of estimating the probability of individuals being included in the sample. Such sample donot use randomization. It relies on personal judgement.

  5. Simple Random Sampling: All members of the group have the same chance of being selected. Sampling with Replacement Sampling without Replacement For Example: If we wish to draw a sample of 10 students from the 10th grade consisting of 50 students. We will place all 50 names in the container and draw out 10 names one by one.

  6. Merits of Simple Random sampling: 1.No personal biases 2.Representative sample 3.More Accuracy in statistical inferences Demerits of Simple Random sampling : 1.Requires specifiable or known universe 2.Requires more money and Time

  7. Stratified Random Sampling: 1.A technique in which whole population is divided into small homogeneous. subgroups known as strata and 2.the respondents are selected randomly by small characteristics in each strata. Finally from each stratum using simple random is used to select the final sample.

  8. Merits of Stratified Random sampling: 1.More Representative. 2.More Precision 3.Detailed information of population Demerits of Stratified Random sampling: 1.Needs too much care in selecting Strata 2.Requires skill and expertize 3.Expensive and time consuming

  9. Cluster Sampling: It is used when population is very large. In it the entire population of interest is divided into groups and groups are selected randomly. In cluster sampling the clusters are primary sampling unit and the units within the clusters are the secondary sampling unit.

  10. Population (Indian Students) Cluster-1 States Random Selection Cluster-2 Universities Cluster-3 Colleges

  11. Merits of Cluster Sampling: 1.Economical and Time Saving 2. Reduces travel and administrative costs Demerits of Cluster Sampling: 1.Standard errors of the estimates are high compared to other sampling design. 2.May not reflect the diversity of universe.

  12. Purposive Sampling: Sample selected which investigator thinks to be most typical of the universe. Also known as judgement or deliberate sampling. Merits & Demerits: 1. Quick studies are done. 2. Economical and Time saving. 3. Require small number of sample units. 1.Less Reliable and less objective. 2. Poor Statistical inferences.

  13. 2. Convenience Sampling: • It involves choosing respondents at the convenience of the researcher.Researcher determines the required sample and simply collects data on that number of individuals who are easily available • Merits: • Low cost • 2. Time saving • 3.Extensively Used. • Demerits: • 1.Restriction of generalization

  14. 3. Snowball Technique: The researcher identifies and selects the available respondents who meet the criteria for being included in the study. Then the researcher asks for the referral of other individuals who meet the criteria. It is also known as chain- sampling or Chain-referral.

  15. Merits of Snowball technique: Access to difficult to reach popution through referrals Time saving Demerits of Snowball technique: 1.It is bised 2. Not representative. 3. Poor statistical inference.

  16. Quota Sampling: It is the process where a researcher gathers data from individuals who possess identified characteristics and quotas. It is just like the stratified sampling except the process of randomization is not done. Merits: Used when budget is low No need of list of population elements required in stratified sampling. Demerits: Time consuming Not Objective.

  17. References (Links) of the Images http://www.datasciencemadesimple.com/wp-content/uploads/2019/06/Stratified-random-sampling-in-R.png https://i.ytimg.com/vi/aomNbRO5Zac/hqdefault.jpg https://tse2.mm.bing.net/th?id=OIP.dCbKaMmNjQcwFJJ5FPuRMQHaFj&pid=Api&P=0&w=224&h=169 Rafi Ullah” Sampling & its types ppt

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