### Foundations in Statistical Reasoning Second Edition

 This is a draft of the second edition.  A pdf version of the text is available at the bottom of this webpage.  This text is licensed with the following creative commons license. Attribution-NonCommercial-ShareAlike CC BY-NC-SA This license lets others remix, tweak, and build upon your work non-commercially, as long as they credit you and license their new creations under the identical terms.               Since this is an open-resource text and since there are many statistics texts on the market, it would not make sense to invest  time and energy on something that can easily be obtained with much less effort.  However, because I wanted a textbook that presented statistics the way I like to teach it, and that approach is significantly different from what is presented in traditional textbooks, I wrote this one.        So how does this differ from traditional books?  It starts by presenting an overview of the statistical thought process.  By the end of chapter 1, students are already familiar with concepts such as hypotheses, level of significance, p-values, errors.  Normally these topics are not introduced until after a discussion of probability and sampling distributions.  My approach to probability and sampling distributions is also very different.  Because students using this book know about hypotheses before we reach the probability section, inferential theory can be developed by applying the probability rules to the testing of a hypothesis. To me, this leads to better and more interesting questions than are typically asked in these sections and gives meaning to these concepts.  Other differences include homework problems that require the integration of topics from different chapters as well as one problem in each chapter based on issues discussed in other classes on our campus (e.g. psychology, criminal justice, economics, etc).Table of ContentsChapter 1  Statistical ReasoningChapter 2  Research Design and Sampling  Chapter 3  Examining the Evidence Using Graphs and StatisticsChapter 4  Inferential TheoryChapter 5  Testing HypothesesChapter 6  Confidence Intervals and Sample SizeChapter 7  Analysis of Bivariate Quantitative DataChapter 8  Chi SquareChapter 9  In-class ActivitiesChapter 10  Effective Communication of Statistical Results Chapter1 provides the overview of the statistical reasoning process and introduce students in an elementary way to the concepts of hypotheses, p-values, errors, writing conclusion.  This is a challenging way to start the quarter because it is actually about how the statistical thought process differs from the algebraic thought processes they are used to.  The challenge is to help the students understand how a decision can be made with only partial information.  That is, we'd like to do a census and find the parameter so we can make the best decision, but we must resort to taking a sample and using the statistic, which can vary, to draw our conclusion.  In spite of the challenges of the first two weeks, the advantage of teaching the statistical thought process early is the students get to use those concepts the entire course.   Chapter 4 takes an entirely different approach than is normally done when learning about probability and sampling distributions.  The goal is to use the probability rules to develop the theory that allows us to test hypotheses.  This is something that can only be done when hypotheses are taught before probability. Chapter 5 presents four different hypothesis tests by showing how the formulas are developed from the same reasoning process.   I am able to finish the entire text in one quarter (50 x 50 minutes) although it is a tight schedule.  The content corresponds to the outcomes at Pierce College (WA).  If your outcomes are different, you may need to find or produce other resources.  My email address is:  pkaslik@pierce.ctc.edu.
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Pete Kaslik,
May 6, 2019, 12:54 PM
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