Rasco, Danney <br/><br/>
An R companion for applied statistics I:   basic bivariate techniques 

 - California  Sage Publications, Inc.  2021 
 - xv, 234 p. 
<br/><br/>Table of content<br/><br/>Chapter 1: Introduction: What is R? <br/>Downloading R and RStudio<br/> <br/>Creating a Project Folder<br/> <br/>Getting Acquainted with the RStudio Environment<br/> <br/>Appendix 1A: Preparing RStudio Project Folder<br/> <br/>  Chapter 2: Basic Tasks in R <br/>Coding in R: Object-Oriented Programming<br/> <br/>Creating Data<br/> <br/>Exporting Data<br/> <br/>Importing Data<br/> <br/>Converting Variables<br/> <br/>Summary of Key Functions<br/> <br/>  Chapter 3: Frequency Tables <br/>Frequency Tables with Quantitative Variables<br/> <br/>Appendix 3A: R Instructions to Accompany Warner (2020a)<br/> <br/>  Chapter 4: Descriptive Statistics <br/>Describing Central Tendency<br/> <br/>Describing Variability<br/> <br/>Appendix 4A: R Instructions to Accompany Warner (2020a)<br/> <br/>Appendix 4B: Mode Function<br/> <br/>  Chapter 5: Visualizing Data: Bar Charts, Histograms, and Boxplots <br/>Visualizing Categorical Variables<br/> <br/>Visualizing Quantitative Variables<br/> <br/>Visualizing and Accounting for a Second Variable<br/> <br/>Appendix 5A: R Instructions to Accompany Warner (2020a)<br/> <br/>  Chapter 6: Evaluating Score Locations: Introducing the Normal Distribution and z Scores <br/>Getting Familiar With New Data Frames and Variables<br/> <br/>Cumulative Percentage<br/> <br/>z Scores<br/> <br/>Addressing Normality<br/> <br/>Appendix 6A: R Instructions to Accompany Warner (2020a)<br/> <br/>  Chapter 7: Sampling Error and Confidence Intervals <br/>Monte Carlo Simulations<br/> <br/>Confidence Intervals<br/> <br/>Appendix 7A: R Instructions to Accompany Warner (2020a)<br/> <br/>  Chapter 8: One-Sample t Test: Introduction to Statistical Significance Tests <br/>Checking Assumptions<br/> <br/>Performing One-Sample t Tests<br/> <br/>Presenting Results<br/> <br/>Considering Alternatives<br/> <br/>Appendix 8A: R Instructions to Accompany Warner (2020a)<br/> <br/>Appendix 8B: One-Sample z Test<br/> <br/>  Chapter 9: Significance Tests Continued: Effect Size and Power <br/>Estimating the Needed Sample Size<br/> <br/>Estimating the Obtained Power<br/> <br/>  Chapter 10: Bivariate Pearson Correlation <br/>Checking Assumptions<br/> <br/>Performing Pearson's Bivariate Correlation<br/> <br/>Considering Alternatives<br/> <br/>Appendix 10A: R Instructions to Accompany Warner (2020a)<br/> <br/>  Chapter 11: Bivariate Regression <br/>Checking Assumptions<br/> <br/>Performing Bivariate Regression<br/> <br/>Appendix 11A: R Instructions to Accompany Warner (2020a)<br/> <br/>  Chapter 12: Independent-Samples t Test <br/>Checking Assumptions<br/> <br/>Performing Independent-Samples t Tests<br/> <br/>Presenting Results<br/> <br/>Considering Alternatives<br/> <br/>Appendix 12A: R Instructions to Accompany Warner (2020a)<br/> <br/>Appendix 12B: Wilcoxon-Mann-Whitney U Test<br/> <br/>  Chapter 13: One-Way Between-Subjects Analysis of Variance <br/>Checking Assumptions<br/> <br/>Performing One-Way Between-Subjects ANOVA Tests<br/> <br/>Presenting Results<br/> <br/>Considering Alternatives<br/> <br/>Appendix 13A: R Instructions to Accompany Warner (2020a)<br/> <br/>  Chapter 14: Paired-Samples t Test <br/>Checking Assumptions<br/> <br/>Performing Paired-Samples t Tests<br/> <br/>Presenting Results<br/> <br/>Considering Alternatives<br/> <br/>Appendix 14A: R Instructions to Accompany Warner (2020a)<br/> <br/>  Chapter 15: One-Way Repeated-Measures Analysis of Variance <br/>Checking Assumptions<br/> <br/>Performing One-Way Repeated-Measures ANOVA Tests<br/> <br/>Presenting Results<br/> <br/>Considering Alternatives<br/> <br/>Appendix 15A: R Instructions to Accompany Warner (2020a)<br/> <br/>  Chapter 16: Factorial Analysis of Variance <br/>Checking Assumptions<br/> <br/>Performing Two-Way Between-Subjects ANOVA Tests<br/> <br/>Presenting Results<br/> <br/>Considering Alternatives<br/> <br/>Appendix 16A: R Instructions to Accompany Warner (2020a)<br/> <br/>Appendix 16B: Converting Education Variable to Dichotomous Variable<br/> <br/>  Chapter 17: Chi-Square (?2) Test of Independence <br/>Checking Assumptions<br/> <br/>Performing Chi-Square (?2) Tests of Independence<br/> <br/>Presenting Results<br/> <br/>Considering Alternatives<br/> <br/>Appendix 17A: R Instructions to Accompany Warner (2020a)<br/> <br/>  Chapter 18: Parting THoughts About R <br/>Moving Forward<br/> <br/>Continuing to Learn R<br/>  
<br/><br/> An R Companion for Applied Statistics I: Basic Bivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use it. R is a powerful, flexible, and free tool. However, the flexibility—which eventually becomes a great asset—can make the initial learning curve appear steep. This book introduces a few key aspects of the R tool. As readers become comfortable with these aspects, they develop a foundation from which to more thoroughly explore R and the packages available for it. This introduction does not explain every possible way to analyze data or perform a specific type of analysis. Rather, it focuses on the analyses that are traditionally included in an undergraduate statistics course and provides one or two ways to run these analyses in R. Datasets and scripts to run the examples are provided on an accompanying website. The book has been designed to be an R companion to Warner's Applied Statistics I, Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide, without reference to the Warner text. 
<br/><br/><label>ISBN: </label>9781071806319 
<br/><br/><label>Subjects--Topical Terms: </label><br/>R (Computer program language)<br/>Commercial statistics<br/>Statistics--Computer programs<br/>Statistics--Data processing
<br/><br/><label>Dewey Class. No.: </label>519.502855133  / RAS