ENGLISH

Learn R for applied Statistics with Data Visualizations, Regressions and Statistics

By Eric Goh Ming Hui

Book information

Publisher
Apress
Year
2019
ISBN
978-1-4842-4200-1
Language
english
Format
PDF
Filesize
6 MB (5796995 bytes)
Pages
250\250
Time added
2018-12-01 13:15:02

Description

Contents......Page 3 Intro......Page 9 What Is R?......Page 10 High-Level and Low-Level Languages......Page 11 What Is Statistics?......Page 12 What Is Data Science?......Page 13 What Is Data Mining?......Page 15 What Is Text Mining?......Page 18 Natural Language Processing......Page 20 Three Types of Analytics......Page 21 Big Data......Page 22 Why R?......Page 24 Conclusion......Page 25 References......Page 27 What Is R?......Page 28 The Integrated Development Environment......Page 29 Installation of R and RStudio......Page 31 Writing Scripts in R and RStudio......Page 39 Conclusion......Page 45 References......Page 46 R Console......Page 47 Code Editor......Page 50 Comments......Page 54 Variables......Page 55 Data Types......Page 56 Vectors......Page 58 Lists......Page 61 Matrix......Page 66 Data Frame......Page 71 Logical Statements......Page 75 Loops......Page 77 Functions......Page 83 Create Calculator......Page 88 Conclusion......Page 91 References......Page 92 What Is Descriptive Statistics?......Page 95 Reading Data Files......Page 96 Basic Data Processing......Page 105 Some Basic Statistics Terms......Page 112 Conclusion......Page 132 References......Page 133 What Are Data Visualizations?......Page 136 Bar Chart and Histogram......Page 137 Line Chart and Pie Chart......Page 144 Scatterplot and Boxplot......Page 149 Scatterplot Matrix......Page 153 Social Network Analysis Graph Basics......Page 154 Using ggplot2......Page 157 ggplot2 Common Charts......Page 165 Interactive Charts with Plotly and ggplot2......Page 173 Conclusion......Page 176 References......Page 177 What Are Inferential Statistics and Regressions?......Page 180 apply(), lapply(), sapply()......Page 182 Sampling......Page 185 Correlations......Page 190 Covariance......Page 192 Hypothesis Testing and P-Value......Page 193 T-Test......Page 194 Chi-Square Test......Page 201 ANOVA......Page 205 Nonparametric Test......Page 216 Linear Regressions......Page 225 Multiple Linear Regressions......Page 230 Conclusion......Page 236 References......Page 238 Index......Page 244

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