# Basic Statistics with R

Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summaries, and relationships between variables - basic probability, and statistical inference - including hypothesis testing and confidence intervals. All topics are taught using real-data drawn from various fields, including economics, biology, political science and sports. Using this wide variety of motivating examples allows students to directly connect and make statistics essential to their field of interest, rather than seeing it as a separate and ancillary knowledge area. In addition to introducing students to statistical topics using real data, the book provides a gentle introduction to coding, having the students use the statistical language and software R. Students learn to load data, calculate summary statistics, create graphs and do statistical inference using R with either Windows or Macintosh machines. Features real-data to give students an engaging practice to connect with their areas of interest Evolves from basic problems that can be worked by hand to the elementary use of opensource R software Offers a direct, clear approach highlighted by useful visuals and examples

Produk Detail:

• Author : Stephen C. Loftus
• Pages : 304 pages
• ISBN : 0128209267
• Rating : 4/5 from 21 reviews

## Basic Statistics with R

• Author : Stephen C. Loftus
• Release : 20 February 2021

Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summaries, and relationships between variables - basic probability, and statistical inference - including hypothesis testing and confidence intervals. All topics are taught using real-data drawn from various fields, including economics, biology, political science and sports. Using this wide variety of motivating examples allows students to directly connect

## Introductory Statistics with R

• Author : Peter Dalgaard
• Publisher : Springer Science & Business Media
• Release : 27 June 2008

This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are

## Using R for Introductory Statistics

• Author : John Verzani
• Publisher : CRC Press
• Release : 03 October 2018

The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic

## Introduction to Data Science

• Author : Rafael A. Irizarry
• Publisher : CRC Press
• Release : 20 November 2019

Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data

## Basic Statistics

• Author : Tenko Raykov,George A. Marcoulides
• Publisher : Rowman & Littlefield
• Release : 16 August 2022

Basic Statistics provides an accessible and comprehensive introduction to statistics using the free, state-of-the-art, powerful software program R. This book is designed to both introduce students to key concepts in statistics and to provide simple instructions for using R. This concise book: .Teaches essential concepts in statistics, assuming little background knowledge on the part of the reader .Introduces students to R with as few sub-commands as possible for ease of use .Provides practical examples from the educational, behavioral, and social

## Modern Statistics with R

• Author : Måns Thulin
• Publisher : BoD - Books on Demand
• Release : 28 July 2021

The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of Modern Statistics with R is to introduce you to key parts of the modern statistical toolkit. It teaches you: - Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. - Exploratory data analysis - using visualisation and multivariate techniques to explore datasets. - Statistical inference - modern methods for testing hypotheses and

## The New Statistics with R

• Author : Andy Hector
• Publisher : Oxford University Press
• Release : 16 August 2022

Statistical methods are a key tool for all scientists working with data, but learning the basic mathematical skills can be one of the most challenging components of a biologist's training. This accessible book provides a contemporary introduction to the classical techniques and modern extensions of linear model analysis: one of the most useful approaches in the analysis of scientific data in the life and environmental sciences. It emphasizes an estimation-based approach that accounts for recent criticisms of the over-use of

## Statistics

• Author : Michael J. Crawley
• Publisher : John Wiley & Sons
• Release : 06 May 2005

Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and

## Biostatistics with R

• Author : Babak Shahbaba
• Publisher : Springer Science & Business Media
• Release : 15 December 2011

Biostatistics with R is designed around the dynamic interplay among statistical methods, their applications in biology, and their implementation. The book explains basic statistical concepts with a simple yet rigorous language. The development of ideas is in the context of real applied problems, for which step-by-step instructions for using R and R-Commander are provided. Topics include data exploration, estimation, hypothesis testing, linear regression analysis, and clustering with two appendices on installing and using R and R-Commander. A novel feature of

## A Course in Statistics with R

• Author : Prabhanjan N. Tattar,Suresh Ramaiah,B. G. Manjunath
• Publisher : John Wiley & Sons
• Release : 15 March 2016

Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R

## An Introduction to Statistical Learning

• Author : Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani
• Publisher : Springer Science & Business Media
• Release : 24 June 2013

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more.

## Easy Statistics for Food Science with R

• Author : Abbas F. M. Alkarkhi,Wasin A. A. Alqaraghuli
• Release : 18 September 2018

Easy Statistics for Food Science with R presents the application of statistical techniques to assist students and researchers who work in food science and food engineering in choosing the appropriate statistical technique. The book focuses on the use of univariate and multivariate statistical methods in the field of food science. The techniques are presented in a simplified form without relying on complex mathematical proofs. This book was written to help researchers from different fields to analyze their data and make

## Statistics With R

• Author : Jenine K. Harris
• Publisher : SAGE Publications
• Release : 19 December 2019

Recipient of a 2021 Most Promising New Textbook Award from the Textbook & Academic Authors Association (TAA) "Statistics with R is easily the most accessible and almost fun introduction to statistics and R that I have read. Even the most hesitant student is likely to embrace the material with this text." —David A.M. Peterson, Department of Political Science, Iowa State University Drawing on examples from across the social and behavioral sciences, Statistics with R: Solving Problems Using Real-World Data introduces foundational

## Statistical Analysis with R For Dummies

• Author : Joseph Schmuller
• Publisher : John Wiley & Sons
• Release : 03 March 2017

Understanding the world of R programming and analysis has never been easier Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses—as well as step-by-step guidance that shows you exactly how to implement them using R programming. People are becoming more aware of R every day as