Learning Statistics with R

Format:

Book

Author/Creator:

Navarro, Danielle, author.

Language:

English

Subjects (All):

Mathematics--Textbooks.

Mathematics.

Social sciences--Textbooks.

Social sciences.

Applied mathematics--Textbooks.

Applied mathematics.

Psychology--Textbooks.

Psychology.

Physical Description:

1 online resource

Place of Publication:

Kensington, Australia Danielle Navarro [2018]

Language Note:

In English.

Summary:

Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book discusses how to get started in R as well as giving an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.

Contents:

I. Background

Chapter 1: Why do we learn statistics?

Chatper 2: A brief introduction to research design

II. An introduction to R

Chapter 3: Getting started with R

Chapter 4: Additional R concepts

III. Working with data

Chapter 5: Descriptive statistics

Chapter 6: Drawing graphs

Chapter 7: Pragmatic matters

Chapter 8: Basic programming

IV. Statistical theory

Prelude

Chapter 9: Introduction to probability

Chapter 10: Estimating unknown quantities from a sample

Chapter 11: Hypothesis testing

V. Statistical tools

Chapter 12: Categorical data analysis

Chapter 13: Comparing two means

Chapter 14: Comparing several means (one-way ANOVA)

Chapter 15: Linear regression

Chapter 16: Factorial ANOVA

VI. Other topics

Chapter 17: Bayesian statistics

Chapter 18: Epilogue

References

Notes:

Description based on print resource