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# 050 sampling theory

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### Transcript of "050 sampling theory"

1. 2. <ul><li>A process of selecting units from a population </li></ul><ul><li>A process of selecting a sample to determine certain characteristics of a population </li></ul><ul><li>A sample is a subset of a larger population of objects individuals, households, businesses, organizations and so forth. </li></ul>Concept of sampling
2. 3. <ul><li>Sampling enables researchers to make estimates of some unknown characteristics of the population in question </li></ul><ul><li>A finite group is called population whereas a non-finite (infinite) group is called universe </li></ul><ul><li>A census is a investigation of all the individual elements of a population </li></ul>
3. 4. 29 Population Sample A sample is a subset of a larger population of objects individuals, households, businesses, organizations and so forth. Sampling enables researchers to make estimates of some unknown characteristics of the population in question A finite group is called population whereas a non-finite (infinite) group is called universe A census is a investigation of all the individual elements of a population
4. 5. <ul><li>Get information about large populations </li></ul><ul><li>Less costs </li></ul><ul><li>Less field time </li></ul><ul><li>More accuracy i.e. Can Do A Better Job of Data Collection </li></ul><ul><li>When it’s impossible to study the whole population </li></ul>Why sampling
5. 6. Classification of Sampling Techniques Probability Sampling Techniques Stratified Sampling Cluster Sampling Simple random Sampling Sampling Techniques Non-probability Sampling Techniques Convenience Sampling Judgment Samples Quota Sampling Snowball Sampling Systematic Sampling
6. 7. <ul><li>Probability Sampling: utilizes some form of random selection. A probability sample is a sample in which every element of the population has a known and equal probability of being selected into the sample. </li></ul><ul><li>Non-probability sampling : does not involve random selection </li></ul>
7. 8. <ul><li>Simple random </li></ul><ul><li>Stratified random </li></ul><ul><li>Systematic random </li></ul><ul><li>Cluster/area random </li></ul><ul><li>Multi-stage random </li></ul>
8. 9. <ul><li>Non-probability Sampling are of following types </li></ul><ul><li>Convenience Sampling Judgment Sampling </li></ul><ul><li>Quota Sampling Snow ball Sampling </li></ul>
9. 10. <ul><li>Probability selected = n i /N </li></ul><ul><li>When population is rather uniform (e.g. school/college students, low-cost houses) </li></ul><ul><li>Simplest, fastest, cheapest </li></ul><ul><li>Could be unreliable, why? </li></ul>A T Y W B P G E S C K L G N Q B T G K Population Sample Population not uniform Wrong procedure ?
10. 11. <ul><li>Pick any “element” </li></ul><ul><li>Use random table </li></ul>
11. 12. <ul><li>Break population into “meaningful” strata and take random sample from each stratum </li></ul><ul><li>Can be proportionate or disproportionate within strata </li></ul><ul><li>When: </li></ul><ul><li>* population is not very uniform (e.g. shoppers, houses) </li></ul><ul><li>* key sub-groups need to be represented -> more </li></ul><ul><li>precision </li></ul><ul><li>* variability within group affects research results </li></ul>1 4 8 12 3 6 13 2 10 20 15 7 14 11 16 3 7 10 16 Population Sample Stratum 2 = even no. Stratum 1 = odd no.
12. 13. <ul><li>Simple or stratified in nature </li></ul><ul><li>Systematic in the “picking-up” of element. E.g. every 5 th . visitor, every 10 th . House, every 15 th . minute </li></ul><ul><li>Steps: </li></ul><ul><li>* Number the population (1,…,N) </li></ul><ul><li>* Decide on the sample size, n </li></ul><ul><li>* Decide on the interval size, k = N/n </li></ul><ul><li>* Select an integer between 1 and k </li></ul><ul><li>* Take case for every k th . unit </li></ul>
13. 14. <ul><li>Research involves spatial issues ( e.g. do prices vary according to neighbourhood’s level of crime? ) </li></ul><ul><li>Sampling involves analysis of geographic units </li></ul><ul><li>Sampling involves extensive travelling -> try to minimise logistic and resources </li></ul><ul><li>Steps: </li></ul><ul><li>* Divide population into “clusters” (localities) </li></ul><ul><li>* Choose clusters randomly (simple random, </li></ul><ul><li>stratified, etc.) </li></ul><ul><li>* Take all cases from each cluster </li></ul><ul><li>Efficient from administrative perspective </li></ul>
14. 15. Section 5 Section 2 Section 1
15. 16. <ul><li>Convenience Samples </li></ul><ul><ul><li>Non-probability samples used primarily because they are easy to collect. </li></ul></ul><ul><li>Judgment Samples </li></ul><ul><ul><li>Non-probability samples in which the selection criteria are based on personal judgment that the element is representative of the population under study. </li></ul></ul>
16. 17. <ul><li>Quota Samples </li></ul><ul><ul><li>Non-probability samples in which population subgroups are classified on the basis of researcher judgment. </li></ul></ul><ul><li>Snowball Samples </li></ul><ul><ul><li>Non-probability samples in which selection of additional respondents is based on referrals from the initial respondents. </li></ul></ul>
17. 19. <ul><li>Thank you! </li></ul>
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