| Description |
1 online resource (513 p.) |
| Series |
Chapman and Hall/CRC Texts in Statistical Science Ser |
|
Chapman and Hall/CRC Texts in Statistical Science Ser
|
| Contents |
Cover -- Half Title -- Title Page -- Copyright Page -- Contents -- Preface -- Software Installation -- 1. Data in R -- 1.1. Arithmetic and variable assignment -- 1.2. Help -- 1.3. Vectors -- 1.4. Indexing vectors -- 1.5. Data types -- 1.6. Data frames -- 1.7. Reading data from files -- 1.8. Packages -- 1.9. Errors and warnings -- 1.10. Useful idioms -- Vignette: Data science communities -- Vignette: An R Markdown primer -- Exercises -- 2. Probability -- 2.1. Probability basics -- 2.2. Simulations -- 2.3. Conditional probability and independence -- 2.4. Counting arguments |
|
Vignette: Negative surveys -- Exercises -- 3. Discrete Random Variables -- 3.1. Probability mass functions -- 3.2. Expected value -- 3.3. Binomial and geometric random variables -- 3.4. Functions of a random variable -- 3.5. Variance, standard deviation, and independence -- 3.6. Poisson, negative binomial, and hypergeometric -- Vignette: Loops in R -- Exercises -- 4. Continuous Random Variables -- 4.1. Probability density functions -- 4.2. Expected value -- 4.3. Variance and standard deviation -- 4.4. Normal random variables -- 4.5. Uniform and exponential random variables -- 4.6. Summary |
|
Exercises -- 5. Simulation of Random Variables -- 5.1. Estimating probabilities -- 5.2. Estimating discrete distributions -- 5.3. Estimating continuous distributions -- 5.4. Central Limit Theorem -- 5.5. Sampling distributions -- 5.6. Point estimators -- Vignette: Stein's paradox -- Exercises -- 6. Data Manipulation -- 6.1. Data frames and tibbles -- 6.2. dplyr verbs -- 6.3. dplyr pipelines -- 6.4. The power of dplyr -- 6.5. Working with character strings -- 6.6. Structure of data -- 6.7. The apply family -- Vignette: dplyr murder mystery -- Vignette: Data and gender -- Exercises |
|
7. Data Visualization with ggplot -- 7.1. ggplot fundamentals -- 7.2. Visualizing a single variable -- 7.3. Visualizing two or more variables -- 7.4. Customizing -- Vignette: Choropleth maps -- Vignette: COVID-19 -- Exercises -- 8. Inference on the Mean -- 8.1. Sampling distribution of the sample mean -- 8.2. Confidence intervals for the mean -- 8.3. Hypothesis tests of the mean -- 8.4. One-sided confidence intervals and hypothesis tests -- 8.5. Assessing robustness via simulation -- 8.6. Two sample hypothesis tests -- 8.7. Type II errors and power -- 8.8. Resampling -- Exercises |
|
9. Rank Based Tests -- 9.1. One sample Wilcoxon signed rank test -- 9.2. Two sample Wilcoxon tests -- 9.3. Power and sample size -- 9.4. Effect size and consistency -- 9.5. Summary -- Vignette: ROC curves and the Wilcoxon rank sum statistic -- Exercises -- 10. Tabular Data -- 10.1. Tables and plots -- 10.2. Inference on a proportion -- 10.3. X2 tests -- 10.4. X2 goodness of fit -- 10.5. X2 tests on cross tables -- 10.6. Exact and Monte Carlo methods -- Vignette: Tables -- Exercises -- 11. Simple Linear Regression -- 11.1. Least squares regression line -- 11.2. Correlation |
| Notes |
Description based upon print version of record |
|
11.3. Geometry of regression |
| Form |
Electronic book
|
| Author |
Clair, Bryan
|
| ISBN |
9781000504514 |
|
1000504514 |
|
