Statistics with R

Statistics with R

使用 R 语言进行统计：初学者指南
统计学史

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作者

Robert Stinerock

出版社

Sage

出版时间

2022年11月07日

装帧

精装

ＩＳＢＮ

9781529753530

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页码

448

语种

英文

版次

2nd ed.

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Statistics is made simple with this award-winning guide to using R and applied statistical methods. With a clear step-by-step approach explained using real world examples, learn the practical skills you need to use statistical methods in your research from an expert with over 30 years of teaching experience. With a wealth of hands-on exercises and online resources created by the author, practice your skills using the data sets and R scripts from the book with detailed screencasts that accompany each script. This book is ideal for anyone looking to: • Complete an introductory course in statistics • Prepare for more advanced statistical courses • Gain the transferable analytical skills needed to interpret research from across the social sciences • Learn the technical skills needed to present data visually • Acquire a basic competence in the use of R and RStudio. This edition also includes a gentle introduction to Bayesian methods integrated throughout. The author has created a wide range of online resources, including: over 90 R scripts, 36 datasets, 37 screen casts, complete solutions for all exercises, and 130 multiple-choice questions to test your knowledge.

Chapter 1: Introduction and R Instructions \ Basic Terminology \ Data: Qualitative or Quantitative \ Data: Cross-Sectional or Longitudinal \ Descriptive Statistics \ Probability \ Statistics: Estimation and Inference \ Chapter 2: Descriptive Statistics: Tabular and Graphical Methods \ Methods of Summarizing and Displaying Qualitative Data \ Methods of Summarizing and Displaying Quantitative Data \ Cross Tabulations and Scatter Plots \ Chapter 3: Descriptive Statistics: Numerical Methods \ Measures of Central Tendency \ Measures of Location \ Exploratory Data Analysis: The Box Plot Display \ Measures of Variability \ The z-Score: A Measure of Relative Location \ Measures of Association: The Bivariate Case \ The Geometric Mean \ Chapter 4: Introduction to Probability \ Some Important Definitions \ Counting Rules \ Assigning Probabilities \ Events and Probabilities \ Probabilities of Unions and Intersections of Events \ Conditional Probability \ Bayes’ Theorem and Events \ Chapter 5: Discrete Probability Distributions \ The Discrete Uniform Probability Distribution \ The Expected Value and Standard Deviation of a Discrete Random Variable \ The Binomial Probability Distribution \ The Poisson Probability Distribution \ The Hypergeometric Probability Distribution \ The Hypergeometric Probability Distribution: The General Case \ Bayes’ Theorem and Discrete Random Variables \ Chapter 6: Continuous Probability Distributions \ Continuous Uniform Probability Distribution \ Normal Probability Distribution \ Exponential Probability Distribution \ Optional Material: Derivation of the Cumulative Exponential Probability Func- tion \ Bayes’ Theorem and Continuous Random Variables \ Chapter 7: Point Estimation and Sampling Distributions \ Populations and Samples \ The Simple Random Sample \ The Sample Statistic: x, s, and p \ The Sampling Distribution of x \ The Sampling Distribution of p \ Some Other Commonly Used Sampling Methods \ Bayes’ Theorem: Approximate Bayesian Computation \ Chapter 8: Confidence Interval Estimation \ Interval Estimate of µ When

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