Lesson 1: Confidence Intervals

Learning Objective: Understand how to construct and interpret confidence intervals for population parameters.

Video Lecture: Introduction to Confidence Intervals

Duration: 15 minutes

Key Point: A 95% confidence interval means that if we repeated our sampling process many times, 95% of the intervals would contain the true population parameter.

Confidence Interval Simulation

Generate samples and observe how confidence intervals behave:

µ = 100
σ = 15
n = 30
Samples Generated: 0
Intervals Containing µ: 0 (0%)

Check Your Understanding

Question: If you calculate 100 90% confidence intervals from different samples, about how many would you expect to contain the true population mean?





Discussion Prompt

After experimenting with the simulation:

  1. What happens to the width of confidence intervals as you increase the sample size?
  2. How does changing the confidence level affect how often the intervals contain the true mean?
  3. Can you create a situation where most confidence intervals don't contain the population mean? How?