R Statistics Cookbook: Over 100 recipes for performing complex statistical operations with R 3.5


R Statistics Cookbook: Over 100 recipes for performing complex statistical operations with R 3.5
By 作者: Francisco Juretig
ISBN-10 书号: 1789802563
ISBN-13 书号: 9781789802566
Release Finelybook 出版日期: 2019-03-29
pages 页数: (448 )

The Book Description

More Information
Learn
Become well versed with recipes that will help you interpret plots with R
Formulate advanced statistical models in R to understand its concepts
Perform Bayesian regression to predict models and input missing data
Use time series analysis for modelling and forecasting temporal data
Implement a range of regression techniques for efficient data modelling
Get to grips with robust statistics and hidden Markov models
Explore ANOVA (Analysis of Variance) and perform hypothesis testing
About
R is a popular programming language for developing statistical software. This book will be a useful guide to solving common and not-so-common challenges in statistics. With this book, you'll be equipped to confidently perform essential statistical procedures across your organization with the help of cutting-edge statistical tools.

You'll start by implementing data modeling, data analysis, and machine learning to solve real-world problems. You'll then understand how to work with nonparametric methods, mixed effects models, and hidden Markov models. This book contains recipes that will guide you in performing univariate and multivariate hypothesis tests, several regression techniques, and using robust techniques to minimize the impact of outliers in data.You'll also learn how to use the caret package for performing machine learning in R. Furthermore, this book will help you understand how to interpret charts and plots to get insights for better decision making.

By the end of this book, you will be able to apply your skills to statistical computations using R 3.5. You will also become well-versed with a wide array of statistical techniques in R that are extensively used in the data science industry.

Features
Learn how to apply statistical methods to your everyday research with handy recipes
Foster your analytical skills and interpret research across industries and business verticals
Perform t-tests, chi-squared tests, and regression analysis using modern statistical techniques

contents
1 Getting Started with R and Statistics
2 Univariate and Multivariate Tests for Equality of Means
3 Linear Regression
4 Bayesian Regression
5 Nonparametric Methods
6 Robust Methods
7 Time Series Analysis
8 Mixed Effects Models
9 Predictive Models Using the Caret Package
10 Bayesian Networks and Hidden Markov Models

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