2.  Questions?
 Population and samples: definitions +
differences
 Review confidence intervals
 Practice problems

3.  Population: “all possible measurements or
outcomes that are of interest to us in a
particular study”
 Sample: “portion of the population that is
representative of the population from which
it was selected”
 Representative v. non-representative sampling

4.  
Is the WSPS a population or a sample?

5.  A confidence interval is an interval estimate
of an unknown population parameter, based
upon a random sample
 Interval estimate: range within the
confidence interval.
 Example: [280, 310]
 What is the point estimate for the above?
 Think of confidence intervals as “plausible
values” for a parameter

6.  Plausible estimate of the range
 For 95% CI, you have a 5% chance of
_______________________________
 Will a 99% CI be wider or narrower than a 95% CI?
 Stability of the estimate itself
 Wider confidence interval around the mean – or
proportion – signals relative instability
 Narrow confidence interval signals relative
stability

7. 

8. 

9. Interpretation of confidence intervals should:
1) Clearly state the confidence level (CL)
2) Explain what population parameter is being
estimated (mean or proportion)
3) Should state the confidence interval (both
endpoints).
 "We estimate with ___% confidence that the true
population mean (include context of the problem) is
between ___ and ___ (include appropriate units).“
(Dean and Ilowksy 2012)

10. Assume that a school district has 10,000 6th
graders. In this district, the average weight of a
6th grader is 80 pounds, with a standard
deviation of 20 pounds. Suppose you draw a
random sample of 50 students. What is the
probability that the average weight of a
sampled student will be less than 75 pounds?