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Sampling. Fair sampling produces a sample which represents the population in all important ways.

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Presentation on theme: "Sampling. Fair sampling produces a sample which represents the population in all important ways."— Presentation transcript:

1 Sampling

2 Fair sampling produces a sample which represents the population in all important ways.

3

4 Constructing a Sample

5 1. Define the general universe.

6 Constructing a Sample 1. Define the general universe. 2. Identify an observable working universe.

7 Constructing a Sample 1. Define the general universe. 2. Identify an observable working universe. 3. Choose the sampling unit.

8 Constructing a Sample 1. Define the general universe. 2. Identify an observable working universe. 3. Choose the sampling unit. 4. Develop or find a sampling frame.

9 Constructing a Sample 1.Define the general universe.

10 Constructing a Sample 1.Define the general universe. U.S. school teachers

11 Constructing a Sample 1.Define the general universe. U.S. school teachers 2. Identify an observable working universe.

12 Constructing a Sample 1.Define the general universe. U.S. school teachers 2. Identify an observable working universe. teachers who belong to national teacher associations

13 Constructing a Sample 1.Define the general universe. U.S. school teachers 2. Identify an observable working universe. teachers who belong to national teacher associations 3. Choose the sampling unit.

14 Constructing a Sample 1.Define the general universe. U.S. school teachers 2. Identify an observable working universe. teachers who belong to national teacher associations 3. Choose the sampling unit. a single teacher

15 Constructing a Sample 1.Define the general universe. U.S. school teachers 2. Identify an observable working universe. teachers who belong to national teacher associations 3. Choose the sampling unit. a single teacher 4. Develop or find a sampling frame.

16 Constructing a Sample 1.Define the general universe. U.S. school teachers 2. Identify an observable working universe. teachers who belong to national teacher associations 3. Choose the sampling unit. a single teacher 4. Develop or find a sampling frame. lists of email addresses of members purchased from the National Education Association and the American Federation of Teachers

17 Survey Jargon

18 From the sampling frame, you choose who to solicit for participation. You ask these people to participate in your study or reply to your survey. Of those you contact and solicit for participation, some will participate and some will not. Those who choose to participate are respondents. Of all those who were solicited, the percentage who became respondents is your response rate. Survey Jargon

19 From the sampling frame, you choose who to solicit for participation. You ask these people to participate in your study or reply to your survey. Of those you contact and solicit for participation, some will participate and some will not. Those who choose to participate are respondents. Of all those who were solicited, the percentage who became respondents is your response rate. Number responding to survey Number solicited for participation Survey Jargon Response Rate =

20 Sampling Strategies

21 random systematic stratified random cluster judgment convenience

22 Sampling Strategies random Number all email addresses and randomly produce numbers systematic stratified random cluster judgment convenience

23 Sampling Strategies random Number all email addresses and randomly produce numbers systematic Pick every 50 th email address. stratified random cluster judgment convenience

24 Sampling Strategies random Number all email addresses and randomly produce numbers systematic Pick every 50 th email address. stratified random Group teachers by teaching level- elementary & secondary. Randomly select from each group. cluster judgment convenience

25 Sampling Strategies random Number all email addresses and randomly produce numbers systematic Pick every 50 th email address. stratified random Group teachers by teaching level- elementary & secondary. Randomly select from each group. cluster Start with a working universe of all schools. Randomly select schools and survey all teachers in that school. judgment convenience

26 Sampling Strategies random Number all email addresses and randomly produce numbers systematic Pick every 50 th email address. stratified random Group teachers by teaching level- elementary & secondary. Randomly select from each group. cluster Start with a working universe of all schools. Randomly select schools and survey all teachers in that school. judgment Recruit the teachers who appear to be in touch with today’s issues. convenience

27 Sampling Strategies random Number all email addresses and randomly produce numbers systematic Pick every 50 th email address. stratified random Group teachers by teaching level- elementary & secondary. Randomly select from each group. cluster Start with a working universe of all schools. Randomly select schools and survey all teachers in that school. judgment Recruit the teachers who appear to be in touch with today’s issues. convenience Recruit the teachers in your school.

28 Sample Size

29 If the research goal is to describe a population, the primary concern when determining a sample size is describing the population with precision.

30 Sample Size If the research goal is to describe a population, the primary concern when determining a sample size is describing the population with precision. The primary concern when determining a sample size is sampling error.

31 Sample Size The larger the sample, the closer the sample values are to the true population values.

32 Sample Size The larger the sample, the closer the sample values are to the true population values. The larger the sample, the smaller the sampling error.

33 Sample Size The larger the sample, the closer the sample values are to the true population values. The larger the sample, the smaller the sampling error. A common formula for calculating sampling error for surveys is the standard error of proportion.

34 Standard Error of Proportion

35

36 Sample Finding Sample Size Proportion1-Proportion Standard Error 72% of 212 sailors have knee trouble. 212.72.28.046

37 Standard Error of Proportion Sample Finding Sample Size Proportion1-Proportion Standard Error 72% of 212 sailors have knee trouble. 212.72.28.046 51% of 1400 voters say they will vote for Bruce Frey for dogcatcher. 1400.51.49.013

38 Standard Error of Proportion Sample Finding Sample Size Proportion1-Proportion Standard Error 72% of 212 sailors have knee trouble. 212.72.28.046 51% of 1400 voters say they will vote for Bruce Frey for dogcatcher. 1400.51.49.013 Because standard errors of proportion are normally distributed, we can create 95% confidence intervals by using +/- 1.96 standard errors.

39 Standard Error of Proportion Sample Finding Sample Size Proportion1-Proportion Standard Error 72% of 212 sailors have knee trouble. 212.72.28.046 51% of 1400 voters say they will vote for Bruce Frey for dogcatcher. 1400.51.49.013 Because standard errors of proportion are normally distributed, we can create 95% confidence intervals by using +/- 1.96 standard errors. Out of all sailors, there is a 95% chance that somewhere between 63% and 81% have knee trouble.

40 Standard Error of Proportion Sample Finding Sample Size Proportion1-Proportion Standard Error 72% of 212 sailors have knee trouble. 212.72.28.046 51% of 1400 voters say they will vote for Bruce Frey for dogcatcher. 1400.51.49.013 Because standard errors of proportion are normally distributed, we can create 95% confidence intervals by using +/- 1.96 standard errors. Out of all sailors, there is a 95% chance that somewhere between 63% and 81% have knee trouble. I am 95% confident, that if we had surveyed all voters, somewhere between 48% and 54% would say they plan to vote for Frey. “Margin of Error: +/- 2.5%”

41 Sampling Problem

42 A researcher is interested in transplant surgeons' attitudes toward a policy initiative that would provide organs to patients most in need of transplants rather than providing organs to patients on the waiting list of hospitals who harvest the organs. The researcher decides to conduct a telephone interview with a random sample of 250 board certified heart transplant surgeons. There are 1000 board certified heart transplant surgeons. Of the 250 heart surgeons included in the sample, 240 were contacted and 220 of them agreed to the telephone interview. 20% of the heart transplant surgeons agree with the statement: Heart transplants should be provided to patients in greatest need.

43 Sampling Problem A researcher is interested in transplant surgeons' attitudes toward a policy initiative that would provide organs to patients most in need of transplants rather than providing organs to patients on the waiting list of hospitals who harvest the organs. The researcher decides to conduct a telephone interview with a random sample of 250 board certified heart transplant surgeons. There are 1000 board certified heart transplant surgeons. Of the 250 heart surgeons included in the sample, 240 were contacted and 220 of them agreed to the telephone interview. 20% of the heart transplant surgeons agree with the statement: Heart transplants should be provided to patients in greatest need. What is the sampling frame?

44 Sampling Problem A researcher is interested in transplant surgeons' attitudes toward a policy initiative that would provide organs to patients most in need of transplants rather than providing organs to patients on the waiting list of hospitals who harvest the organs. The researcher decides to conduct a telephone interview with a random sample of 250 board certified heart transplant surgeons. There are 1000 board certified heart transplant surgeons. Of the 250 heart surgeons included in the sample, 240 were contacted and 220 of them agreed to the telephone interview. 20% of the heart transplant surgeons agree with the statement: Heart transplants should be provided to patients in greatest need. What is the response rate?

45 Sampling Problem A researcher is interested in transplant surgeons' attitudes toward a policy initiative that would provide organs to patients most in need of transplants rather than providing organs to patients on the waiting list of hospitals who harvest the organs. The researcher decides to conduct a telephone interview with a random sample of 250 board certified heart transplant surgeons. There are 1000 board certified heart transplant surgeons. Of the 250 heart surgeons included in the sample, 240 were contacted and 220 of them agreed to the telephone interview. 20% of the heart transplant surgeons agree with the statement: Heart transplants should be provided to patients in greatest need. What is the standard error of proportion?

46 Sampling Problem

47 A school district wishes to conduct a survey to assess alcohol use by its students. A random sample of all students (equal numbers of boys and girls) will be solicited for participation and asked if they drink beer on the week-ends. The evaluators consult with you to determine an adequate total sample size. Assume you wish to have a margin of error of +/- 5%. What sample size would you suggest? Use the default assumption of 50% (Yes’s or No’s) for your estimates.

48 Sampling Problem Assume you wish to have a margin of error of +/- 5%. What sample size would you suggest? Use the default assumption of 50% (Yes’s or No’s) for your estimates. Sample Size Proportion1-Proportion Proportion * 1-Proportion Standard Error Margin of Error (1.96* SE) 100.50.50.25.05.098 200.50.50.25.0353.069 300.50.50.25.029.057 400.50.50.25.025.049 390.50.50.25.0253.05 Margin of error =.05.05/1.96 =.0255, so I want a Standard Error of around.0255

49 Sampling Problem Assume you wish to have a margin of error of +/- 5%. What sample size would you suggest? Use the default assumption of 50% (Yes’s or No’s) for your estimates. Margin of error =.05.05/1.96 =.0255, so I want a Standard Error of around.0255

50 Sampling Problem Assume you wish to have a margin of error of +/- 5%. What sample size would you suggest? Use the default assumption of 50% (Yes’s or No’s) for your estimates. Sample Size Proportion1-Proportion Proportion * 1-Proportion Standard Error Margin of Error (1.96* SE) 100.50.50.25.05.098 200.50.50.25.0353.069 300.50.50.25.029.057 400.50.50.25.025.049 390.50.50.25.0253.05 Margin of error =.05.05/1.96 =.0255, so I want a Standard Error of around.0255

51 Sampling Problem

52


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