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Dataframe manipulation with tidyr

Learning objective:  To understand the concepts of ‘long’ and ‘wide’ data formats and be able to convert between them with tidyr.

Part of a software carpentry online course R for reproducible scientific analysis.

Dataframe manipulation with tidyr

R for reproducible scientific analysis

Software Carpentry

Data:

Gapminder dataset

Gapminder dataset (wide format)

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Drew LaMar onto Data Manipulation in R

Cheat Sheet: Data Wrangling with dplyr and tidyr

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Drew LaMar onto Data Manipulation in R

Data Processing with dplyr & tidyr, by Brad Boehmke

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Drew LaMar onto Data Manipulation in R

The goal of the cookbook is to provide solutions to common tasks and problems in analyzing data.

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Drew LaMar onto Internet resources for learning R

Learn to use R: Your hands-on guide

by Sharon Machlis
edited by Johanna Ambrosio

Computerworld

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Drew LaMar onto Internet resources for learning R

simpleR - Using R for Introductory Statistics

These notes are an introduction to using the statistical software package R for an introductory statistics course. They are meant to accompany an introductory statistics book such as Kitchens “Exploring Statistics”. The goals are not to show all the features of R, or to replace a standard textbook, but rather to be used with a textbook to illustrate the features of R that can be learned in a one-semester, introductory statistics course.

Download

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Drew LaMar onto Books About Using R

Chapter 3 – The R Programming Language

Chapter from "Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan (Second Edition)" by John K. Kruschke

Proxy Access

  1. R

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Drew LaMar onto Books About Using R

R Base Graphics: An Idiot's Guide

Last year, I presented an informal course on the basics of R Graphics University of Turku. In this blog post, I am providing some of the slides and the full code from that practical, which shows how to build different plot types using the basic (i.e. pre-installed) graphics in R

Website Supplementary Files

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Drew LaMar onto Data Visualization in R

How to format plots for publication using ggplot2

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Drew LaMar onto Data Visualization in R

Creating publication quality graphs in R

by Tim Appelhans

This tutorial was developed as part of a one-day workshop held within the Ecosystem Informatics PhD-programme at the Philipps University of Marburg. The contents of this turtorial are published under the creatice commons license 'Attribution-ShareAlike CC BY-SA'.

Website

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Drew LaMar onto Data Visualization in R

Visual ANOVA

Created by Thomas Malloy (requires Flash)

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Drew LaMar onto Visualizing Statistics

Visualizing a One-Way ANOVA using D3.js

A while ago I was playing around with the JavaScript package D3.js, and I began with this visualization—that I never really finished—of how a one-way ANOVA is calculated. I wanted to make the visualization interactive, and I did integrate some interactive elements. For instance, if you hover over a data point it will show the residual, and its value will be highlighted in the combined computation. The circle diagram show the partitioning of the sums of squares, and if you hover a part it will show from where the variation is coming. I tried to make the plots look like plots from the R-package ggplot2.

Created by Kristoffer Magnusson

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Drew LaMar onto Visualizing Statistics

Understanding Statistical Power and Significance Testing: An Interactive Visualization

This visualization is meant as an aid for students when they are learning about statistical hypothesis testing. The visualization is based on a one-sample Z-test. You can vary the sample size, power, signifance level and effect size using the sliders to see how the sampling distributions change.

Created by Kristoffer Magnusson

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Drew LaMar onto Visualizing Statistics

Statistical Power and Significance Testing (R Shiny App)

Note:  To run this visualization, you need a QUBES account.  Click here to register (it's free!)

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Drew LaMar onto Visualizing Statistics

Central Limit Theorem

From the authors of the textbook:

We have put together a few interactive animations that will illustrate some important statistics concepts (with funding from the University of British Columbia). These are all released into the public domain, so anyone can use them as they wish. Click on the “tutorial” button to be walked through the concepts, or just explore them on your own.

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Drew LaMar onto Visualizing Statistics

Confidence limits for the mean

From the authors of the textbook:

We have put together a few interactive animations that will illustrate some important statistics concepts (with funding from the University of British Columbia). These are all released into the public domain, so anyone can use them as they wish. Click on the “tutorial” button to be walked through the concepts, or just explore them on your own.

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Drew LaMar onto Visualizing Statistics

Sampling means from a normal distribution

From the authors of the textbook:

We have put together a few interactive animations that will illustrate some important statistics concepts (with funding from the University of British Columbia). These are all released into the public domain, so anyone can use them as they wish. Click on the “tutorial” button to be walked through the concepts, or just explore them on your own.

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Drew LaMar onto Visualizing Statistics

Chapter 18: Multiple explanatory variables

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Drew LaMar onto Chapter-by-chapter resources

Chapter 17: Regression

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Drew LaMar onto Chapter-by-chapter resources

Chapter 16: Correlation between numerical variables

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Drew LaMar onto Chapter-by-chapter resources

Chapter 15: The analysis of variance

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Drew LaMar onto Chapter-by-chapter resources

Chapter 13: Handling violations of assumptions

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Drew LaMar onto Chapter-by-chapter resources

Chapter 12: Comparing two means

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Drew LaMar onto Chapter-by-chapter resources

Chapter 11: Inference for a normal population

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Drew LaMar onto Chapter-by-chapter resources