Web Visualization: Sampling from a Normal distribution

Prerequisite Knowledge

Students should

• be familiar with methods of summarizing data sets, such as mean and standard deviation;
• be able to recognize probability models as distributions with shape, centre, and spread;
• be able to recall the key properties of the Normal model.

Learning Objectives

• Identify and distinguish between a population and a sample, and between parameters and statistics
• Interpret histograms for summarizing and comparing data sets
• Explain the concepts of sampling variability and sampling distribution
• Describe properties of the sampling distribution of the sample mean
• Explain whether and how the population distribution and the sample size influence the sampling distribution of the sample mean from a Normal distribution

Suggested use(s) and tips

These resources are intended to be used in a number of ways,

• as a visual aid during lectures;
• as an open-ended learning tool for active learning;
• as a guided learning experience, using either the built-in tutorials, guided activity sheet (click here for Instructor Guide and Activity Sheet), or other instructor-supplied material.

About this resource

Funding: University of British Columbia
Project Leader: Mike Whitlock
Programmers: Boris Dalstein, Mike Whitlock & Zahraa Almasslawi
Art: Derek Tan
Testing: Melissa Lee, Gaitri Yapa & Bruce Dunham
Thanks to: Darren Irwin, Dolph Schluter, Nancy Heckman, Kaylee Byers, Brandon Doty, Kim Gilbert, Sally Otto, Wilson Whitlock, Jeff Whitlock, Jeremy Draghi, Karon MacLean, Fred Cutler, Diana Whistler, Andrew Owen, Mike Marin, Leslie Burkholder, Eugenia Yu, Doug Bonn, Michael Scott, the UBC Physics Learning Group & the UBC Flex Stats initiative for numerous suggestions and improvements.