Resource Library

The purpose of this activity is to enhance students' understanding of various descriptive measures. In particular, by completing this hands-on activity students will experience a visual interpretation of a mean, median, outlier, and the concept of distance-to-mean.

By means of a simple story and a worksheet with questions we guide the students from research question to arriving at a conclusion. The whole process is simply reasoning, no formulas. We use the reasoning already done by the student to introduce the standard vocabulary of testing statistical hypotheses (null & alternative hypotheses, p-value, type I and type II error, significance level). Students need to be familiar with binomial distribution tables. After the ducks story is finished, the class is asked to come up with their own research question, collect the data, do the hypotheses testing and answer their own research question. The teaching material is intended to be flexible depending of the time available. Instructors can choose to do just the interactive lecture type, interactive lecture + activity, or even add the optional material.

This hands-on activity is appropriate for a lab or discussion section for an introductory statistics class, with 8 to 40 students. Each student performs a binomial experiment and computes a confidence interval for the true binomial probability. Teams of four students combine their results into one confidence interval, then the entire class combines results into one confidence interval. Results are displayed graphically on an overhead transparency, much like confidence intervals would be displayed in a meta-analysis. Results are discussed and generalized to larger issues about estimating binomial proportions/probabilities.

In this hands-on activity, students count the number of chips in cookies in order to carry out an independent samples t-test to see if Chips AhoyŒ¬ cookies have a higher, lower, or different mean number of chips per cookie than a supermarket brand. First there is a class discussion that can include concepts about random samples, independence of samples, recently covered tests, comparing two parameters with null and alternative hypotheses, what it means to be a chip in a cookie, how to break up the cookies to count chips, and of course a class consensus on the hypotheses to be tested. Second the students count the number of chips in a one cookie from each brand, and report their observations to the instructor. Third, the instructor develops the independent sample t-test statistic. Fourth, the students carry out (individually or as a class) the hypothesis test, checking the assumptions on sample-size/population-shape.

Tutorial on the ANOVA test in statistics and probability, with a description, formulas, example, and a calculator applet. This is part of the larger site Virtual Statistician at http://web.mst.edu/~psyworld/virtualstat.htm

November 24, 2009 Activity webinar presented by Carl Lee, Central Michigan University, and hosted by Leigh Slauson, Capital University. This webinar introduces a real-time online hands-on activity database for teaching introductory statistics. One particular activity, "How well can hand size predict height?", is used to engage students with a real-time activity in order to learn bivariate relationships. Various other activities can be found at stat.cst.cmich.edu/statact. The real-time database approach speeds up the process of data gathering and shifts the focus in order to engage students in the process of data production and statistical investigation.

In this game activity, students match correlation values with plots generated by the applet. Competition in this game setting encourages students to become more involved in the classroom and attainment of learning objectives. This game is best if used in a lab setting, although it may be modified to fit other classroom situations.

This activity will allow students to familiarize themselves with technology and its use in calculating marginal, conditional, and joint distributions, as well as making conclusions from these tabular and graphical displays. The corresponding data set 'Pizza Data' is located at the following web address: http://www.causeweb.org/repository/ACT/PIZZA.TXT

This activity provides practice for constructing confidence intervals and performing hypothesis tests. In addition, it stresses interpretation of confidence intervals and comparison and application of results in context.

This activity stresses the importance of writing clear, unbiased survey questions. It explore the types of bias present in surveys and ways to reduce these biases. In addition, the activity covers some basics of surveys: population, sample, sampling frame, and sampling method.