Estimation and probability

Using a sample to make a guess and a guess about your guess

Objective

To introduce students to how data can be used to estimate parameters of interest and associated sampling error. By the end of the lesson, you should be able to

• explain how sampling error is estimated (conceptually and via formulas) for various distributiond

• develop and interpret 95% confidence intervals

Background reading

Course notes links for background reading also contain code used to produce R output used in slides.

• https://jsgosnell.github.io/cuny_biostats_book/content/chapters/Estimation.html

Lecture slides (click to open in Google slides!)

Extra material

• Maintaining Standards: Differences between the Standard Deviation and Standard Error, and When to Use Each
  • a helpful journal article
• Tutorials produced by a group at UBC tha help visualize sampling, confidence intervals, and the central limit theorm
  • Sampling from a normally distributed population
  • Confidence intervals for the mean
  • Sampling from a non-Normally distributed population (the central limit theorem)