更新时间：2021-07-02 18:44:27
封面
书名页
Statistical Application Development with R and Python - Second Edition
Credits
About the Author
Acknowledgment
About the Reviewers
www.PacktPub.com
eBooks discount offers and more
Customer Feedback
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Chapter 1. Data Characteristics
Questionnaire and its components
Experiments with uncertainty in computer science
Installing and setting up R
Using R packages
Python installation and setup
IDEs for R and Python
The companion code bundle
Discrete distributions
Continuous distributions
Summary
Chapter 2. Import/Export Data
Packages and settings – R and Python
Understanding data.frame and other formats
Using utils and the foreign packages
Exporting data/graphs
Pop quiz
Chapter 3. Data Visualization
Visualization techniques for categorical data
Visualization techniques for continuous variable data
Pareto chart
A brief peek at ggplot2
Chapter 4. Exploratory Analysis
Essential summary statistics
Techniques for exploratory analysis
Chapter 5. Statistical Inference
Maximum likelihood estimator
Confidence intervals
Hypothesis testing
Chapter 6. Linear Regression Analysis
Packages and settings - R and Python
The essence of regression
The simple linear regression model
Multiple linear regression model
Regression diagnostics
Model selection
Chapter 7. Logistic Regression Model
Model validation and diagnostics
Logistic regression for the German credit screening dataset
Chapter 8. Regression Models with Regularization
Regression spline
Ridge regression for linear models
Chapter 9. Classification and Regression Trees
Splitting the data
Chapter 10. CART and Beyond
Understanding bagging
Index
