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Barbara Illowsky | De Anza College |
Susan Dean | De Anza College |
Alexander Holmes | Regent's Professor of Economics University of Oklahoma |
Kevin Hadley | Analyst, Federal Reserve Bank of Kansas City |
Mathew Price | Research Assistant, University of Oklahoma |
OpenStax College’s Introductory Statistics by senior contributing writers Barbara Illowsky and Susan Dean is a complete text in itself and thus the creation of a custom edition requires some rationale for all the effort that went into its creation.
This custom edition for the University of Oklahoma builds directly upon Introductory Statistics and maintains, for the most part, the structure of the material. Only does the order of the latter chapters on the Chi squared distribution and the F distribution change. The discrete probability density functions have been reordered in what is felt helps provide a logical development of probability density functions from simple counting formulas to more complex continuous distributions. What has been preserved and is a true foundation stone of both texts are the homework assignments and examples. Many additional homework assignments have been added and new examples that use a more mathematical approach are in the new text, but the wealth of examples, mostly with answers, are critical to student success and a keystone to the OU’s custom edition of Introductory Statistics .
What differentiates this text from its foundation document grows out of a difference in philosophy toward the use of mathematical formulas. The significant and important work of the foundation text to help students master the Texas Instruments calculator has been discarded. All required calculations are within the capability of a $2.00 calculator, until regression, correlation and ANOVA, of course. It is my belief that students lose much if they do not see the formulas in action and develop a “feel” for what they are doing with the data. This requires additional material that helps students understand the combinatorial formula and factorials as well as sigma notation otherwise carried by the calculator. This difference in perspective then changes the acceptance/rejection rule for hypothesis testing to comparisons between calculated test statistics verse p-values. The terminology of confidence intervals, and the process of finding probabilities also changes including now the reliance upon statistical tables not required when probabilities are produced by the TI-83, 83+, 84 or 84+.
Laying more emphasis on the development of the mathematical formulas requires a closer link to the fundamental theorem of inferential statistics, the Central Limit Theorem. This relationship is developed in the foundation text and given its proper critical role in statistical theory. The OU custom edition of Introductory Statistics repeats this link in each section for each test statistic developed; test for proportions, for differences in means and differences in proportions.
Perhaps the greatest difference in the two texts is in the development of regression and correlation analysis. This arises from the second important philosophical perspective the custom edition emphasizes; the link between statistical inference and the scientific method. As an Economist, regression is the tool toward which this whole text is directed although this text is directed more broadly than toward Economics majors. Economics models are fundamentally grounded in assumed relationships of cause and effect. They are developed to both test hypotheses about cause and effect and to predict from such models. This comes from the belief that statistics is the gatekeeper allowing some theories to remain and others to be cast aside for a new perspective of the world around us. This philosophical view is presented in detail throughout and informs the method of presenting the regression model, in particular.
The original correlation and regression chapter has been essentially replaced and dramatically expanded to include confidence intervals for predictions, alternative mathematical forms to allow for testing categorical variables, and the presentation of the multiple regression model.
This OU custom edition Introductory Statistics owes much to the work of Dr. Illowsky and Ms. Dean in OpenStax College’s Introductory Statistics and it is hereby acknowledged with thanks. Indeed, even in their title they foreshadow the creation of this text.
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