Why do we need statistics?

Objective

To introduce students (to the class and field of statistics) and discuss how we can acquire and summarize data. By the end of the lesson, you should be able to

• discuss why scientists need statistics

• define statistics

• understand the structure of the course

• discuss what sampling is (and how it relates to statistics)

• discuss what makes a good sample

• define bias and provide examples of sampling schemes that may lead to it

• provide examples of how data can be numerically and visually summarized and discuss best practices for these deciding on how specific data sets should be summarized

  • Note you don’t have to “make” the graphs or produce the calculations! We’ll do those in later sessions - focus on the concepts for now

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/getting_started/getting_started.html

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

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

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

Lecture slides (click to open in Google slides!)

Extra material

Polling problems and why we should still trust some polls

Visualize residuals with help of this app produced by a group at UBC.