Summary: The EXCEL STATISTICS COMPANION CD-ROM AND MANUAL, VERSION 2.0 is a collection of demonstrations, sampling experiments, and interactive exercises that dovetails with traditional textbook coverage of descriptive and inferential statistics. The materials give students the hands-on experience they need to master abstract statistical concepts and computational procedures. Microsoft® Excel®'s spreadsheet capabilities for data generation and instant dynamic response ...show more to user input provide a platform for teaching statistics that goes beyond the usual verbal and visual textbook explanations. All the workbooks on this CD-ROM contain detailed on-screen instructions. For Microsoft® Windows® and Excel novices, additional documentation (with extensive use of screen captures) appears in the companion ESC USER'S MANUAL. Carefully coordinated with the workbooks, the USER'S MANUAL begins with a basic skills workbook that reviews the limited subset of Excel and Windows skills needed to navigate and run the main body of programs. VERSION 2.0 includes four new workbooks and several new worksheets within existing workbooks, as well as a line-by-line edit to increase clarity and streamline pedagogy.
New to the Edition
A new demo worksheet ("an empirical proof") has been added at the end of workbook 1-1. Using the data selected at the beginning of the workbook, this additional worksheet shows empirically that the sum of the deviations from the mean equals zero and the sum of the squared deviations equals a minimum. Using any constant different from the mean cannot yield the zero/minimum result. This demonstrates two properties of the mean: the value about which the sum of the deviations is zero and the value about which the sum of the squared deviations is a minimum.
"Solving Problems" (workbook 5-2) is a new workbook that provides opportunities to compute probabilities using the addition and multiplication rules. Students configure a basket of red, white, and blue balls (for example, ten red balls, five white, and two blue) and questions are posed regarding the probabilities associated with different possible samples. The solutions, which appear on adjacent worksheets, are dynamically linked to student's basket configuration, so Excel provides the correct answers to the problems no matter how many balls of each color the student initially decides to put in the basket. This feature allows for extensive practice applying the addition and multiplication computational rules.
The second new workbook (8-3 "Unplanned Comparisons") is an interactive exercise showing why special "post hoc" data analyses are required to keep the probability of Type 1 error under control when doing unplanned (a posteriori/post hoc) comparisons among multiple samples. Both the independent- and related-samples scenarios are covered.
The third new workbook (7-3 Paired-Samples t test) covers the paired-samples t test. The statistical output is dynamically linked to the data, which allows exploring the relationship between existing correlation, within-sample variability, effect size, and the t-test results. The presentation includes the representation of a paired-samples t test as a single-sample t test computed on the array of difference scores.
The fourth new "capstone" workbook (11-1 Test Selection) provides a representative variety of research scenarios along with data. The student's job is to choose and compute the statistic that is both appropriate for the data and will answer the researcher's question. Only two data sets appear: two columns for the first series of problems and four columns for the second series. Using the same data for several problems drives home the point that the appearance of data (two or four columns) is generally not a useful cue when deciding on the correct data analysis. This feature encourages students to focus on the scaling of the data and the nature of the research question.
The data for the problems are dynamically linked to the solutions, so the solutions, which may be seen by scrolling to the right of each worksheet, are updated instantly following any changes to either data set. This allows limitless opportunity to practice the steps of data analysis for each type of problem as well as the opportunity to practice the interpretation of various patterns of results.
Workbook 9-4 now has a streamlined introduction and a new practice problem with data dynamically linked to the solution. The practice problem is the same one presented in the Exercise packet. With the dynamic calculation feature, students may change the original data on the hard-copy exercise and explore the ANOVA and chart results for the mixed design that apply to the new data. This allows not only computational practice (comparing one's own ANOVA and chart to the solutions) and linking features of data (variability, effect size) to the ANOVA output, but also practice in interpreting the many different possible patterns of results students may create.
Rosenberg revised workbooks 10-1 (Chi Sq. Goodness of Fit), 10-3 (Mann-Whitney), and 10-4 (Wilcoxon) to add more opportunities for practice and more dynamic calculations for running exploratory "what if" changes to the data. He also added worksheets and did some redesigning of displays in workbooks 10-3 and 10-4 to make the presentations more complete and improve pedagogy.
This CD-ROM/manual package allows communication of statistical concepts through automated sampling experiments and the spreadsheet capability for instantly updating statistics, table entries, and charts in response to user inputs. The USER'S MANUAL supplements the on-screen instructions with additional text and images (full and partial "screen captures") of all relevant menus and dialog boxes. This step-by-step approach makes clear exactly what the user's screen should look like at any stage of a session.
The initial workbooks help students gain an intuitive grasp of the statistics of central tendency and variability, including the creation and interpretation of charts and tables.
Demonstrations illustrate the properties and usefulness of the z statistic, followed by a template for problem-solving practice.
Automated sampling experiments show patterns of association (zero, positive, and negative), the consequences of violating the assumptions that underlie the Pearson r statistic, and examples of Type 1 and Type 2 errors when determining the significance of the Pearson r statistic. Rosenberg also uses automated sampling experiments to compare theoretical and empirical sampling distributions of the binomial and the distribution of the sample mean (central limit theorem).
Rosenberg illustrates the fitting of the regression line to the scatterplot with automated sampling experiments as well as with dynamic calculations and charts that respond instantly to changes the user makes to the resident data set.
Using Excel's paste functions, the CD-ROM demonstrates the process of computing probability in the context of the binomial and normal distributions (z statistic) along with a useful platform for practice problem solving. The CD-ROM also uses Excel to compute confidence intervals and, using sampling experiments, illustrates the effect of sample size on the width of the confidence interval and the logic and theory that underlies the construction of 95 percent confidence intervals.
In the context of the t statistic and the analysis of variance (ANOVA), automated displays invite the user to manipulate treatment effects and within-sample variability and instantly assess the impact of these features of data on the determination of statistical significance.
Rosenberg explains the logic of hypothesis testing (including null hypothesis, alternative hypothesis, statistical significance, Type 1 error, Type 2 error, and effect size), and, using Excel-generated empirical data, demonstrates both correct and incorrect (Type 1 and 2 errors) statistical decisions.
The user controls sample size, effect size, and within-sample variability to demonstrate how resulting statistical power, or lack thereof, affects the accuracy of statistical decisions based on the two-sample t test, one-way ANOVA, or two-way ANOVA. The two-way ANOVA worksheet also contains a chart that is instantly responsive to the user's input.
Rosenberg illustrates (through a sampling experiment and subsequent data transformations) how the two-way analysis of variance (ANOVA) reflects the existence of no experimental effects (null hypothesis true), as well as a significant A main effect, a B main effect, and some potential patterns of A x B interaction. Charts and tables update instantly following user-controlled systematic changes to the resident data set.
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