Fluent Python

Fluent Python: Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best and possibly most neglected features. Author Luciano Ramalho takes you through Python’s core language features and libraries, … Read more

Linear Models with R

Linear Models with R: There are many books on regression and analysis of variance. These books expect different levels of preparedness and emphasise the material. This book is not introductory. It presumes some knowledge of basic statistical theory and practice. Readers are expected to know the essentials of statistical inference such as estimation, hypothesis testing … Read more

Introduction To Statistical Data Analysis With R

This book offers an introduction to statistical data analysis by applying the free statistical software R, probably the most powerful statistical software today. The analyses are performed and discussed using real data. After a brief description of the statistical software R, important parameters and diagrams of descriptive statistics are introduced. Subsequently, recommendations for generating diagrams … Read more

Natural Language Processing with Python

This Book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open-source library. If you’re interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages or are curious about a programmer’s perspective on how human language works, you’ll find both fascinating … Read more

Python Machine Learning By Example

Python Machine Learning By Example, Third Edition serves as a comprehensive gateway into the world of machine learning (ML). With six new chapters, on topics including movie recommendation engine development with Naive Bayes, recognizing faces with support vector machine, predicting stock prices with artificial neural networks, categorizing images of clothing with convolutional neural networks, predicting … Read more

Python for Probability Statistics and Machine Learning

Python for Probability Statistics and Machine Learning fully updated for Python version 3.6+ covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas.  All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working with … Read more

Learning Statistics with R

Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on using the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R and introduces 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.

Learning Statistics with R
Learning Statistics with R

Author

Danielle Navarro, PhD is a computational cognitive scientist at the University of New South Wales. Her research focuses on human concept learning, reasoning and decision-making. She is also interested in language and cultural evolution, cognitive development, and statistical methods in the behavioural sciences

Contents

A brief introduction to research design11
Getting started with37
857
Additional R concepts73
Working with data111
Drawing graphs157
Pragmatic matters195
Basic programming253
22368
25375
Comparing two means381
33392
35403
Comparing several means oneway ANOVA427
Linear regression459
Factorial ANOVA499
Introduction to Probability275
Estimating unknown quantities from a sample301
1327
14348
Categorical data analysis351
18360
66532
Bayesian statistics557
Epilogue589
69599
Copyright