Resource Library

Document (pdf) illustrating a test of normality using an Anderson-Darling test in MINITAB and a test of equality of variances with an F-test in EXCEL.

This is a complete lesson module (including example problems with answers to selected problems) for the purpose of enabling students to: 1) Provide examples demonstrating how the margin of error, effect size, and variability of the outcome affect sample size computations. 2) Compute the sample size required to estimate population parameters with precision. 3) Interpret statistical power in tests of hypothesis. 4) Compute the sample size required to ensure high power when hypothesis testing.

A game to help in the active learning of concepts in experimental design, regression, and significance testing. Shapesplosion is an on-line game in which a person is expected to place specifically shaped pegs into the appropriate holes within a short time period. In this project, students are asked to use the Shapesplosion game to design an experiment and collect data. This game is specifically designed so that students have the opportunity to develop and test their own unique research question. You can leave all the variables blank when you are simply trying out the game, however, if you want to find your score is the database of results, you will need to select the Participant Info box. This resource is particularly suitable for project oriented teaching and is part of the Stat2Labs collection at Grinnell College that includes instructor notes and student handouts created with funding from NSF-DUE grant #1043814 (Shonda Kuiper, PI).

A game for the active learning of concepts in experimental design and hypothesis testing in the one sample, two-sample and matched pairs situation. Memorathon is an on-line game in which a person is expected to repeat a sequence of buttons provided by an electronic device. Each time you successfully repeat the given sequence of buttons, the sequence gets longer. The challenge is to remember as long a sequence as possible. Cognitive psychologists test short-term memory using serial recall, which evaluates the ability of people to recall information in the specified order in which it was presented. Measuring how many items a subject can remember in order without an error, called memory span, is also studied. The Memorathon Game is an example of serial recall and memory span. This on-line game provides students the opportunity to design multiple versions of the Memorathon Game in order to test which variables have the largest effect on memory. You can leave all the variables blank when you are simply trying out the game, however, if you want to find your score in the database of results, input any specific course ID and student ID. Memorathon is part of the Stat2Labs collection at Grinnell College which includes instructor notes and student handouts.

A game to aid in the active learning of significance testing including power and the limitations of p-values. Statistically Grounded is an on-line game that introduces multivariate issues in a simplified game environment. Students are asked to serve as a consultant for their friend, Joe. Joe is starting his own coffee company and students help him design a study to determine whether factors, such as location, time of day, price, type of music, or some combination of these influence sales. The on-line game allows students to design a study, sample data, and make suggestions on how Joe's business should be run. The game then simulates several months of business based on student's suggestions. The goal is to design a plan that will earn the most sales and make the largest amount of profits. The TigetSTAT labs handouts were created by Rod Sturdivant (Ohio State University) and John Jackson (West Point) as part of the Stat2Labs collection at Grinnell College

A quote to be used in discussing how sufficient data should be able to trump an hypothesis. The quote is by English philosopher and pioneering feminist Mary Wollstonecraft (1759 – 1797) from her 1792 book "A Vindication of the Rights of Woman." .

A quote that might be used in discussing the research cycle where data is gathered in order to reduce uncertainty, which in turn leads to refinement of models and a new quest to reduce remaining uncertainty. The quote is by American educator and classicist Edith Hamilton (1867 – 1963) from her book Spokesmen for God (1949). The quote may also be found at www.quotationsbywomen.com.

A quote to aid in discussing drawing meaning out of data and the ethical presentation of results. The quote is from Susan Etlinger (1962 - ) an industry analyst for the Altimeter Group from her September 2014 TED talk.

A quote to aid in a discussion of drawing out the salient features of data in plots and statistics. The quote is by small business and organization expert Stephanie Winston from her book The Organized Executive: A Program for Productivity--New Ways to Manage Time, Paper, People, and the Digital Office (1994)

A quote to help in discussing over-interpretation of the results of an analysis (e.g. improper extrapolation, unwarranted conclusions that don't match the design of the study, neglecting the true variability in the data, etc.). The quote is by American nonfiction author and science reporter for the New York Times Natalie Angier (1958 - ). The quote is from her book: The Canon: A Whirligig Tour of the Beautiful Basics of Science (2007). The quote may also be found at www.quotationsbywomen.com. In context, the quote reads: "The power of science lies in its willingness to attack a big problem by dividing it into many small pieces, its embrace of the unfairly maligned practice known as reductionism. At the same time, the piecemeal approach demands that scientists be circumspect to an often tedious degree and that they resist – no matter how much they are pushed by their university’s public relations department or by desperate journalists – making more of the data than the data make of themselves."