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Présentation Statistical Analysis With R For Dummies Format Broché
- Livre Technologie
Résumé : The easy, practical guide to R R is powerful, free software for statistical analysis?full of many tools and functions. R makes it possible to carry out complex statistical analyses by simply entering a few commands. This practical, step-by-step guide explains foundational statistical concepts and shows you how to implement them. You'll be able to perform analyses, understand their implications and results, and make them available to a wide audience. Inside...
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Biographie: Introduction 1 About This Book 1 Similarity with This Other For Dummies Book 2 What You Can Safely Skip 2 Foolish Assumptions 2 How This Book Is Organized 3 Part 1: Getting Started with Statistical Analysis with R 3 Part 2: Describing Data 3 Part 3: Drawing Conclusions from Data 3 Part 4: Working with Probability 3 Part 5: The Part of Tens 4 Online Appendix A: More on Probability 4 Online Appendix B: Non-Parametric Statistics 4 Online Appendix C: Ten Topics That Just Didn't Fit in Any Other Chapter 4 Icons Used in This Book 4 Where to Go from Here 5 Part 1: Getting Started with Statistical Analysis with R 7 Chapter 1: Data, Statistics, and Decisions 9 The Statistical (and Related) Notions You Just Have to Know 10 Samples and populations 10 Variables: Dependent and independent 11 Types of data 12 A little probability 13 Inferential Statistics: Testing Hypotheses 14 Null and alternative hypotheses 14 Two types of error 15 Chapter 2: R: What It Does and How It Does It 17 Downloading R and RStudio 18 A Session with R 21 The working directory 21 So let's get started, already 22 Missing data 26 R Functions 26 User-Defined Functions 28 Comments 29 R Structures 29 Vectors 30 Numerical vectors 30 Matrices 31 Factors 33 Lists 34 Lists and statistics 35 Data frames 36 Packages 39 More Packages 42 R Formulas 43 Reading and Writing 44 Spreadsheets 44 CSV files 46 Text files 47 Part 2: Describing Data 49 Chapter 3: Getting Graphic 51 Finding Patterns 51 Graphing a distribution 52 Bar-hopping 53 Slicing the pie 54 The plot of scatter 55 Of boxes and whiskers 56 Base R Graphics 57 Histograms 57 Adding graph features 59 Bar plots 60 Pie graphs 62 Dot charts 62 Bar plots revisited 64 Scatter plots 67 Box plots 71 Graduating to ggplot2 71 Histograms 72 Bar plots 74 Dot charts 75 Bar plots re-revisited 78 Scatter plots 82 Box plots 86 Wrapping Up 89 Chapter 4: Finding Your Center 91 Means: The Lure of Averages 91 The Average in R: mean() 93 What's your condition? 93 Eliminate $-signs forth with() 94 Exploring the data 95 Outliers: The flaw of averages 96 Other means to an end 97 Medians: Caught in the Middle 99 The Median in R: median() 100 Statistics ? la Mode 101 The Mode in R 101 Chapter 5: Deviating from the Average 103 Measuring Variation 104 Averaging squared deviations: Variance and how to calculate it 104 Sample variance 107 Variance in R 107 Back to the Roots: Standard Deviation 108 Population standard deviation 108 Sample standard deviation 109 Standard Deviation in R 109 Conditions, Conditions, Conditions 110 Chapter 6: Meeting Standards and Standings 111 Catching Some Z's 112 Characteristics of z-scores 112 Bonds versus the Bambino 113 Exam scores 114 Standard Scores in R 114 Where Do You Stand? 117 Ranking in R 117 Tied scores 117 Nth smallest, Nth largest 118 Percentiles 118 Percent ranks 120 Summarizing 121 Chapter 7: Summarizing It All 123 How Many? 123 The High and the Low 125 Living in the Mo...
Sommaire: Joseph Schmuller, PhD, has taught undergraduate and graduate statistics, and has 25 years of IT experience. The author of four editions of Statistical Analysis with Excel For Dummies and three editions of Teach Yourself UML in 24 Hours (SAMS), he has created online coursework for Lynda.com and is a former Editor in Chief of PC AI magazine. He is a Research Scholar at the University of North Florida....
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