Learners calculate the amount of pesticide residue in selected foods for two pesticides and determine if these levels are safe. They read an article about a research study looking for metabolites of these pesticides in children. Finally,...

Students identify biotic and abiotic factors which may alter the observed patterns in plant communities with different structural characteristics, climate, or environmental constraints.

Students study drag and how it affects a parachute in the sky.  In this parachutes instructional activity students build models and compare their drag. 

A comprehensive primer in assessment literacy that seeks to raise awareness of key aspects about tests and testing issues. Explains essential statistical terms associated with testing (mean, modes, medians, distribution, dispersion,...

Provides a detailed look at hypothesis testing. The topic is defined and discussed, important points to know about the topic are presented, and finally the "model" is looked at. An easy-to-understand explanation.

The online course consists of educational materials about probability and statistics. Lecture notes, exams, and assignments are included.

Show that you have mastery over the idea behind hypothesis testing by calculating some probabilities and drawing conclusions. Students receive immediate feedback and have the opportunity to try questions repeatedly, watch a video or...

Students can use a Monte Carlo method to collect data. This data, along with an area model of pi, will be used to approximate pi.

High level detailed steps including null hypothesis, alternative hypothesis, significance level, statistics, probability value and statistical significance.

The American Council on Education provides facts and statistics about the GED and the people who have taken it. Enter the site to find this information.

The necessary vocabulary from Richland Community College for statistical hypothesis testing is provided here. After viewing the vocabulary, click the link returning the user to the Table of Contents to see the rest of the Chapter 9 notes...

Students perform chi-square tests to see if data follows a hypothesized distribution. They also study the two-way table analysis.

The use of performance enhancing drugs is the dark side of sport, and there are stringent measures in place to try to screen athletes. But what's the likelihood that an athlete who fails a drug test has actually taken the banned drug?...

[Free Registration/Login may be required to access all resource tools.] This Concept introduces students to testing variance using the chi-square distribution as well as creating a confidence interval for the variance.

Look at the results of different experiments, and determine if they are statistically significant. Students receive immediate feedback and have the opportunity to try questions repeatedly, watch a video or receive hints.

[Free Registration/Login may be required to access all resource tools.] This Concept demonstrates the process of hypothesis testing, using both test statistics and p-values. It also explains type I and II errors.

[Free Registration/Login may be required to access all resource tools.] This Concept introduces students to testing a claim about a proportion.

[Free Registration/Login may be required to access all resource tools.] This Concept introduces students to testing a claim about linear regression.

A page from the university's statistics site which builds on the standard errors from the Central Limit Theorem previously explained. Here hypothesis testing is defined and validated.

Site explains what one-tail and two-tail hypothesis testing are. Includes graphs to aid in understanding.

A good description of hypothesis testing. Refers to the null hypothesis as a "straw man" that is either left standing or knocked down. Other links are provided to related parts of the topic.

This set covers the logic of significance/hypothesis tests. Students decide whether a one- or two-tailed test is appropriate. They also decide, by comparing the p-value to the alpha level, whether statistically significant evidence exists.

[Free Registration/Login may be required to access all resource tools.] This Concept uses the t-distribution to test hypotheses for two samples.

[Free Registration/Login may be required to access all resource tools.] This Concept demonstrates how to test a claim about a mean.