Simulating Confidence Intervals
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MERLOT II




        

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Simulating Confidence Intervals

        

Simulating Confidence Intervals

Logo for Simulating Confidence Intervals
This applet allows users to generate confidence intervals for either means or proportions.  Users set the parameters including the number of samples and click "Sample."  The applet graphs the intervals such that intervals containing the true mean or proportion are in green, while intervals not containing the true mean or proportion are in red.  The true mean or proportion is shown by a blue line.
Material Type: Simulation
Date Added to MERLOT: October 09, 2006
Date Modified in MERLOT: August 13, 2012
Authors:
Send email to arossman@calpoly.edu
Send email to bchance@calpoly.edu
Submitter: Ginger Rowell

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About

Primary Audience: College General Ed
Mobile Compatibility: Not specified at this time
Language: English
Cost Involved: no
Source Code Available: no
Accessiblity Information Available: no
Creative Commons: unsure

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Avatar for Josh Errickson
3 years ago

Josh Errickson (Faculty)

This is used by students in an Intro class, without instructor interaction. Easy for them to use, and illustrates several key ideas.

Used in course

Avatar for David Childers
6 years ago

David Childers (Student)

Going through the steps of the problems posed in this applet should serve to help students be able to identify all the necessary information to perform a hypothesis test. This applet does not use the p-value approach but rather compares the z-score to a z-critical value.

Avatar for David Childers
6 years ago

David Childers (Student)

This applet has features (including a running total of confidence intervals covering the true parameter value and the sort option) which could potentially help a student better understand the concepts of confidence interval and level. One detail worth mentioning: you can see that the width of the confidence intervals differ when using the 't' option. An instructor could use this as an opportunity to illustrate that different samples will have different sample standard deviations.