Interval Estimation

Lecture Demo

Dr. Elijah Meyer

Duke University
STA 199 - Fall 2023

2024-01-29

Checklist

Before class starts, I pull up a checklist of information that students may reference to help best situate them in and outside of class. Items often include:

– Be checking Slack

– Clone the in-class activity from GitHub

– Due Dates

Warm Up Questions

– Typically between 1-3 questions

– Provide students a “no stakes” assessment on previous material

– Students are encouraged to work alone, or in a group setting

Example Warm Up: Notation

Population vs Sample

– What the difference?

– How does notation change for the following:

— Mean

— Proportion

— Slope

Example Warm Up

– When do we create confidence intervals?

– When do we conduct a hypothesis test?

Confidence Intervals

– are a range of plausible values that our population parameter could be

– we make confidence intervals when we want to ESTIMATE

Confidence Intervals

By the end of class, we will

– conceptually understand bootstrapping for a difference in means

– code this method in R

ae-demo

Summary Statistic

iris_filter |>
  group_by(Species) |>
  summarise(mean_sep = mean(Sepal.Length))

In Summary

– Let research guide my practice

– Adapt to class size/structure

– Have a conversation with students

– Build a community + learn together