1. Stat 217 – Day 2
Selecting Samples (3.2)

2. Announcements Complete survey Computer usage rules
Studio open hours TR 10am-12, W 6-8pm
Questions on syllabus?
warning about coursenotes
Advice for doing well in course
8-12 hours/week
“participate in class,” “stay on top of material,” “ask questions”

3. Last Time
Examining numerical information with a critical eye!

4. Last Time Collecting your own data
1. Defining variables/observational units
characteristic that changes from individual to individual
quantitative vs. categorical
2. Deciding on the measurement tools, definitions
3. Choosing the individuals
population vs. sample

5. Example 1-5: Sampling CP Students
Sampling frame
registration list
addresses from Cal Poly website
(b) Variables
GPA (what is your GPA? average GPA?)
major (what is your major? most population major?)
whether or not the student smokes (vs. percentage that smoke)

6. Example 1-6: Chocolate Lovers
(a) lifespan = quantitative
chocolate eating habits = categorical?
smoking habits = categorical?
weight = quantitative
(b) 7,841 Harvard male graduates
(c) men
(d) bias?
(e) cause and effect?

7. BIAS
The sampling design is biased if sample tends to overrepresent certain segments of the population
Justify why you believe the sample results will lead to an overestimate or an underestimate of the actual value for the population.

8. BIAS
Common sources
convenience samples
voluntary response
nonresponse
bad “sampling frame”
If we want our result to “represent” the population, have to be very careful when we try to select our sample

9. Today
How do we select our subset so we believe the sample is representative of the population?
“representative” = has the same characteristics

10. Example 2-1: Sampling Words
Do you think the lengths in your sample of 10 words is representative of the lengths in the population?
How decide?

11. Example 2-1: Sampling Words
Population = all 268 words in the Gettysburg Address
Sample = 10 words you selected
Compare the proportion of long words in your samples to the population proportion
(f) 99 long words
population proportion = 99/268 =.369

12. Class Results “Dotplot” = each dot represents one of your samples
Bias = systematic tendency to choose longer words,
overestimated the proportion of long words
population
proportion
(i) Why?

13. Better Ways to Select Sample
Need list of every member of population
“sampling frame”
Example: telephone books, vehicle registration lists not a good choice in 1930s
Example: registrar’s list
2. Number every member of the list
statweb.calpoly.edu/chance/stat217/address.html

14. Better Ways to Select Sample
Table B
Read off 3 digit numbers until you have 5
Skip numbers > 268
Eliminate any repeat numbers
Report the corresponding “individuals”

15. Better Ways to Select Sample
Combine results
To examine long-run properties
statweb.calpoly.edu/chance/applets/applets.html

16. Behavior of Samples
If randomly select the samples, results will not be biased
Though results vary from sample to sample, are not consistently off in the same direction
Results from larger samples are closer together
Increases precision, does not decrease bias
Population size does not matter!

17. Random Sampling Error
Is variability from sample to sample around the population value
will be able to measure the amount of random sampling error
example 2-3
sample size is what matters, not population size or proportion of population sampled
Example: Tasting soup

18. Does this solve all of our problems?

19. Does this solve all of our problems?
Nonsampling errors = select a random sample but then…
missing data
response errors
lying
nonvoters
undecided
response bias (sensitive question)
wording of the question
processing errors

20. Overcoming nonsampling errors
Repeat visits
Insure confidentiality
Test different wordings
Change order of choices
Give background material/encourage respondents to admit they don’t know
Control appearance of interviewer

21. Lab 1 Start analyzing data population sample descriptive statistics
inference
evaluate some conjecture about the population

22. Lab 1 Variable: choose Coke or Pepsi?
Summary: how many students choose Coke?
Is this convincing evidence that a majority of students prefer one soda over the other?

23. Assignments By Friday By Monday Complete Blackboard survey
Look through Lab 1 and bring floppy disk
Finish HW 1