Teaching Statistics Wiley Online Library : Teaching Statisticshttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2F%28ISSN%291467-9639John Wiley & Sons, Incen© Teaching Statistics Trust0141-982X1467-96392013-06-01T00:00:00-05:00Summer 201335277111Bringing Data to Life into an Introductory Statistics Course with Gapminderhttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12015Bringing Data to Life into an Introductory Statistics Course with GapminderDai-Trang Le2013-06-11T02:52:36.993465-05:00doi:10.1111/test.12015John Wiley & Sons, Inc.10.1111/test.12015http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12015Original Articlen/an/aSummary

Gapminder is a free and easy to use software for visualising real-world data in multiple dimensions. The simple format of the Cartesian coordinate system is used in a dynamic and interactive way to convey a great deal of information. This tool can be readily used to arouse students' natural curiosity regarding world events and to increase the motivation to understand statistics.

]]> Gapminder is a free and easy to use software for visualising real-world data in multiple dimensions. The simple format of the Cartesian coordinate system is used in a dynamic and interactive way to convey a great deal of information. This tool can be readily used to arouse students' natural curiosity regarding world events and to increase the motivation to understand statistics.Technology-enhanced Interactive Teaching of Marginal, Joint and Conditional Probabilities: The Special Case of Bivariate Normal Distributionhttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12012Technology-enhanced Interactive Teaching of Marginal, Joint and Conditional Probabilities: The Special Case of Bivariate Normal DistributionIvo D. Dinov, Scott Kamino, Bilal Bhakhrani, Nicolas Christou2013-05-23T02:26:14.674805-05:00doi:10.1111/test.12012John Wiley & Sons, Inc.10.1111/test.12012http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12012Original Articlen/an/aSummary

Data analysis requires subtle probability reasoning to answer questions like What is the chance of event A occurring, given that event B was observed? This generic question arises in discussions of many intriguing scientific questions such as What is the probability that an adolescent weighs between 120 and 140 pounds given that they are of average height? and What is the probability of (monetary) inflation exceeding 4% and housing price index below 110? To address such problems, learning some applied, theoretical or cross-disciplinary probability concepts is necessary. Teaching such courses can be improved by utilizing modern information technology resources. Students' understanding of multivariate distributions, conditional probabilities, correlation and causation can be significantly strengthened by employing interactive web-based science educational resources. Independent of the type of a probability course (e.g. majors, minors or service probability course, rigorous measure-theoretic, applied or statistics course) student motivation, learning experiences and knowledge retention may be enhanced by blending modern technological tools within the classical conceptual pedagogical models.

We have designed, implemented and disseminated a portable open-source web-application for teaching multivariate distributions, marginal, joint and conditional probabilities using the special case of bivariate Normal distribution. A real adolescent height and weight dataset is used to demonstrate the classroom utilization of the new web-application to address problems of parameter estimation, univariate and multivariate inference.

]]> Data analysis requires subtle probability reasoning to answer questions like What is the chance of event A occurring, given that event B was observed? This generic question arises in discussions of many intriguing scientific questions such as What is the probability that an adolescent weighs between 120 and 140 pounds given that they are of average height? and What is the probability of (monetary) inflation exceeding 4% and housing price index below 110? To address such problems, learning some applied, theoretical or cross-disciplinary probability concepts is necessary. Teaching such courses can be improved by utilizing modern information technology resources. Students' understanding of multivariate distributions, conditional probabilities, correlation and causation can be significantly strengthened by employing interactive web-based science educational resources. Independent of the type of a probability course (e.g. majors, minors or service probability course, rigorous measure-theoretic, applied or statistics course) student motivation, learning experiences and knowledge retention may be enhanced by blending modern technological tools within the classical conceptual pedagogical models. We have designed, implemented and disseminated a portable open-source web-application for teaching multivariate distributions, marginal, joint and conditional probabilities using the special case of bivariate Normal distribution. A real adolescent height and weight dataset is used to demonstrate the classroom utilization of the new web-application to address problems of parameter estimation, univariate and multivariate inference.Editorialhttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12009Editorial2013-04-02T04:02:28.22997-05:00doi:10.1111/test.12009John Wiley & Sons, Inc.10.1111/test.12009http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12009Editorial7777The danger of dichotomizing continuous variables: A visualizationhttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12006The danger of dichotomizing continuous variables: A visualizationOliver Kuss2013-04-02T04:02:28.22997-05:00doi:10.1111/test.12006John Wiley & Sons, Inc.10.1111/test.12006http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12006ORIGINAL ARTICLE7879Abstract

Four rather different scatterplots of two variables X and Y are given, which, after dichotomizing X and Y, result in identical fourfold-tables misleadingly showing no association.

]]> Four rather different scatterplots of two variables X and Y are given, which, after dichotomizing X and Y, result in identical fourfold-tables misleadingly showing no association. A limitation with least squares predictionshttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Fj.1467-9639.2012.00512.xA limitation with least squares predictionsTeresa L. Bittner2012-03-06T06:37:05.818237-05:00doi:10.1111/j.1467-9639.2012.00512.xJohn Wiley & Sons, Inc.10.1111/j.1467-9639.2012.00512.xhttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Fj.1467-9639.2012.00512.xORIGINAL ARTICLE8083Abstract

Although researchers have documented that some data make larger contributions than others to predictions made with least squares models, it is relatively unknown that some data actually make no contribution to the predictions produced by these models. This article explores such noncontributory data.

]]> Although researchers have documented that some data make larger contributions than others to predictions made with least squares models, it is relatively unknown that some data actually make no contribution to the predictions produced by these models. This article explores such noncontributory data. Using the coefficient of determination R2 to test the significance of multiple linear regressionhttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Fj.1467-9639.2012.00525.xUsing the coefficient of determination R2 to test the significance of multiple linear regressionRoberto C. Quinino, Edna A. Reis, Lupércio F. Bessegato2012-07-30T00:16:33.794348-05:00doi:10.1111/j.1467-9639.2012.00525.xJohn Wiley & Sons, Inc.10.1111/j.1467-9639.2012.00525.xhttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Fj.1467-9639.2012.00525.xORIGINAL ARTICLE8488Abstract

This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling.

]]> This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. How much is it going to cost me to complete a collection of football trading cards?http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12005How much is it going to cost me to complete a collection of football trading cards?Oke Gerke2013-04-02T04:02:28.22997-05:00doi:10.1111/test.12005John Wiley & Sons, Inc.10.1111/test.12005http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12005ORIGINAL ARTICLE8993Abstract

Trading cards for various sports and a range of other subjects such as architecture, animals, hobbies, and war have been in existence since the late nineteenth century and still enjoy great popularity. Two of the most prominent examples are baseball cards in the U.S. and football cards in Europe. Three strategies for collecting European football trading cards were investigated for two different groups: either a single collector or two collectors joining forces. An activity is proposed in which students use a simulation to compute the factor by which the number of trading cards bought exceeds the number to be collected. This enables them to estimate the expected costs of completing a collection of trading cards. The overall expected costs vary considerably, depending on the strategy used. Savings for a team of two collectors as opposed to a single collector are indicated.

]]> Trading cards for various sports and a range of other subjects such as architecture, animals, hobbies, and war have been in existence since the late nineteenth century and still enjoy great popularity. Two of the most prominent examples are baseball cards in the U.S. and football cards in Europe. Three strategies for collecting European football trading cards were investigated for two different groups: either a single collector or two collectors joining forces. An activity is proposed in which students use a simulation to compute the factor by which the number of trading cards bought exceeds the number to be collected. This enables them to estimate the expected costs of completing a collection of trading cards. The overall expected costs vary considerably, depending on the strategy used. Savings for a team of two collectors as opposed to a single collector are indicated. Figuring out the statistics of the ICC World Cup 2011http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12007Figuring out the statistics of the ICC World Cup 2011Jyoti P. Shiwalkar, M.N. Deshpande2013-04-02T04:02:28.22997-05:00doi:10.1111/test.12007John Wiley & Sons, Inc.10.1111/test.12007http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12007ORIGINAL ARTICLES9497Abstract

This paper deals with the analysis of cricket match results from the ICC World Cup 2011. We believe that such data provide good material for interesting classroom exercises.

]]> This paper deals with the analysis of cricket match results from the ICC World Cup 2011. We believe that such data provide good material for interesting classroom exercises. Online course design: a statistics course examplehttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Fj.1467-9639.2012.00523.xOnline course design: a statistics course exampleSuzan Gazioğlu2012-07-30T00:14:55.929518-05:00doi:10.1111/j.1467-9639.2012.00523.xJohn Wiley & Sons, Inc.10.1111/j.1467-9639.2012.00523.xhttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Fj.1467-9639.2012.00523.xORIGINAL ARTICLE98102Abstract

Classroom-based learning has great value, but online classes are becoming quite popular in the academic world because of the tremendous opportunities they offer. This article outlines the author's journey through the planning, development and execution of an online statistics course.

]]> Classroom-based learning has great value, but online classes are becoming quite popular in the academic world because of the tremendous opportunities they offer. This article outlines the author's journey through the planning, development and execution of an online statistics course. Weighted Means Through the Looking Glasshttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Fj.1467-9639.2011.00475.xWeighted Means Through the Looking GlassRuma Falk, Avital Lavie Lann2011-04-28T05:28:08.334053-05:00doi:10.1111/j.1467-9639.2011.00475.xJohn Wiley & Sons, Inc.10.1111/j.1467-9639.2011.00475.xhttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Fj.1467-9639.2011.00475.xORIGINAL ARTICLE103106Abstract

Each weighted mean of two values has a counterpart, equidistant from the arithmetic mean, obtained by exchanging roles between the weights or by inversing each weight. These elementary relations are apt for introductory courses.

]]> Each weighted mean of two values has a counterpart, equidistant from the arithmetic mean, obtained by exchanging roles between the weights or by inversing each weight. These elementary relations are apt for introductory courses. Retracted: On a Patrol Problemhttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12011Retracted: On a Patrol Problem2013-04-02T04:02:28.22997-05:00doi:10.1111/test.12011John Wiley & Sons, Inc.10.1111/test.12011http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12011Retracted106106Statistical Diversionshttp://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12008Statistical DiversionsPeter Petocz, Eric Sowey2013-04-02T04:02:28.22997-05:00doi:10.1111/test.12008John Wiley & Sons, Inc.10.1111/test.12008http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Ftest.12008STATISTICAL DIVERSIONS107111