1. Sampling Design

2. But First a Sampling Experiment Each group of students should: 1. Pull 5 candies out of the bag 2. Weigh the candies 3. Write down the weight 4. Put the candies back in the bag!! 5. Pass the scale and bag to your neighbors 6. Silently multiply the weight of the 5 candies by 20.

3. TypeWeight (g) Hersheys43 Hot tamales14 Jr mint18 peanut butter kiss7 Carmels8

4. Discussion

5. Definitions Sampling  procedure involving parts of the whole population Sample  a subset of the pop. Population  finite group of elements Universe  infinite group of elements

6. Why Sample? Pragmatic reasons  Cheaper  Easier  Faster Accurate and reliable results Census?

7. Sampling Define the target population A sampling frame – Mailing lists Reverse directories lists streets and the people that live on them Sampling frame error when the entire population is not represented in the sampling frame Sampling unit- Single

9. Random Sampling Error vs. Nonsampling (Systematic) Error Random Sampling Error  The difference between the sample results and the results of a census using the same methods Systematic error  errors that are not due to chance fluctuations. Sampling frame error is a systematic error.

10. Probability vs. Non-probability sampling Nonprobability- the probability of any particular member of the population being chosen is unknown. Therefore there are no appropriate statistical techniques for measuring random sampling error from a nonprobability sample. Thus making inference is inappropriate.

11. Non-probability Sampling Convenience Sampling  do you have a pulse?

12. Non-probability Sampling Judgment sampling  using your judgment to select the characteristics of interest

13. Non-probability Sampling Quota sampling  a min number of individuals with a certain characteristic.

14. Non-probability Sampling Snowball sampling  initial respondents selected with probability methods, and they refer others

15. Probability Sampling Simple random sampling –  everyone in pop has an equal probability of being selected

16. Probability Sampling Systematic Sampling-  using every 50 th name in a phone book after a random starting point is selected.  Sampling interval- in this case 50  Periodicity- when the names are not ordered randomly

17. Probability Sampling Stratified sampling (increase homogeniety within strata, increase heterogeniety between strata)  Proportional vs. disproportional strata  Optimal allocation

18. Probability Sampling Cluster sampling  Area sample  Multistage area sampling

19. Statistics When sampling is not simple random sampling the statistics get much harder, ie more complex. Observations need to be weighted based upon their probability of appearing in the sample.

20. What is the appropriate sample design?

21. But First a Sampling Experiment Each group of students should: 1. Pull 5 candies out of the bag 2. Weigh the candies 3. Write down the weight 4. Put the candies back in the bag!! 5. Pass the scale and bag to your neighbors 6. Silently multiply the weight of the 5 candies by 20.

22. No Scale Candy Sample TypeWeight (g) Nestle Crunch43.9 3 Musketeers60.4 3 Musketeers Mint35.2 Salted Nut Roll51 Twizzlers14 Starburst5 Tootsie Rolls6.66 Milk Duds12 Peppermint Patties17

23. No Scale Candy Sample TypeWeight (g) Twix56.7 Reese’s “Big Cup”39 Gum5.6 Milky Way17 Rolo6

24. No Scale Candy Sample TypeWeight (g) Crunch43.9 Heath14 Milk Duds12 3 Muskateers60 Hot Tamales14