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050 sampling theory
- 2. A process of selecting units from a population A process of selecting a sample to determine certain characteristics of a population A sample is a subset of a larger population of objects individuals, households, businesses, organizations and so forth. Concept of sampling
- 3. 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. 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
- 5. Get information about large populations Less costs Less field time More accuracy i.e. Can Do A Better Job of Data Collection When it’s impossible to study the whole population Why sampling
- 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
- 7. 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. Non-probability sampling : does not involve random selection
- 8. Simple random Stratified random Systematic random Cluster/area random Multi-stage random
- 9. Non-probability Sampling are of following types Convenience Sampling Judgment Sampling Quota Sampling Snow ball Sampling
- 10. Probability selected = n i /N When population is rather uniform (e.g. school/college students, low-cost houses) Simplest, fastest, cheapest Could be unreliable, why? 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 ?
- 11. Pick any “element” Use random table
- 12. Break population into “meaningful” strata and take random sample from each stratum Can be proportionate or disproportionate within strata When: * population is not very uniform (e.g. shoppers, houses) * key sub-groups need to be represented -> more precision * variability within group affects research results 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.
- 13. Simple or stratified in nature Systematic in the “picking-up” of element. E.g. every 5 th . visitor, every 10 th . House, every 15 th . minute Steps: * Number the population (1,…,N) * Decide on the sample size, n * Decide on the interval size, k = N/n * Select an integer between 1 and k * Take case for every k th . unit
- 14. Research involves spatial issues ( e.g. do prices vary according to neighbourhood’s level of crime? ) Sampling involves analysis of geographic units Sampling involves extensive travelling -> try to minimise logistic and resources Steps: * Divide population into “clusters” (localities) * Choose clusters randomly (simple random, stratified, etc.) * Take all cases from each cluster Efficient from administrative perspective
- 15. Section 5 Section 2 Section 1
- 16. Convenience Samples Non-probability samples used primarily because they are easy to collect. Judgment Samples Non-probability samples in which the selection criteria are based on personal judgment that the element is representative of the population under study.
- 17. Quota Samples Non-probability samples in which population subgroups are classified on the basis of researcher judgment. Snowball Samples Non-probability samples in which selection of additional respondents is based on referrals from the initial respondents.
- 19. Thank you!