R resources
Never done any coding before? Need to know how to download R and get started? These resources are for you.
First steps in R
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1. Downloading R and R studio
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A guide to downloading R and RStudio, the two pieces of software you will need for working in R.
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2. Opening R and RStudio for the first time
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Here we introduce the RStudio environment and begin to explore the ways in which we can interact with it.
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3. Beginning to interact with R
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How to enter your first instructions into the RStudio environment.
- 4. Objects and functions in R
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Here we introduce the key ideas of objects and functions in the R environment. We look at how to define objects and call functions.
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5. More about vectors
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This video continues on from "Objects and Functions" Parts 1 and 2. There is continued discussion of vectors in R, how to define them and different categories of vector.
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6. Matrices
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The first video defines a matrix is and how to create one in R. The second defines character matrices and spotting errors in the definition of a matrix.
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7. Creating Dataframes
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Introducing dataframes in R. How to make a dataframe from scratch in RStudio.
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8. Installing packages
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What a package is and how to install a package to RStudio
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9. Swirl
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Swirl is a package designed for learning R interactively in RStudio. This video shows you how to install and begin using it.
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10. Viewing built-in datasets
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How to access and begin to manipulate the datasets in the "datasets" package which is installed by default with RStudio.
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11. More objects
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A guide to some more types of objects in the R environment.
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12. Functions for getting to know a dataset
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A quick tour of a few useful functions which help you to get a feel for a dataset in RStudio.
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13. Importing data
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Video 1: A quick guide to preparing and saving data using an excel spreadsheet before importing it into RStudio.
Video 2: How to get data into RStudio in the form of a data frame once the data have been prepared in an excel spreadsheet and saved in as a CSV file.
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14. Where to go next...
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The last video in the "First Steps in R" series. This video is intended to show the viewer some resources for continuing their learning of R.
Further R resources
Summarising categorical variables
Summarising categorical variables using charts and tables in R.
Chi-squared test for association
Chi-squared test for association between two categorical variables in R.
Summarising continuous data using summary measures and charts in R.
Guide to checking Normality using plots and tests in R.
How to undertake the paired t-test in R.
Wilcoxon (matched pairs) signed-rank test
Guide to undertaking the Wilcoxon (matched pairs) signed-rank test in R.
Guide to undertaking the independent samples t-test in R.
Guide to undertaking the Mann-Whitney U test in R.
One-way (between groups) analysis of variance
Guide to undertaking the one-way (between groups) analysis of variance.
Guide to undertaking the Kruskall-Wallis test in R.
Two-way (between groups) analysis of variance
Guide to undertaking a two-way (between groups) analysis of variance in R.
Guide to dealing with interactions for a single continuous outcome with two categorical independent variables.
Guide to undertaking an analysis of covariance in R.
Repeated measures analysis of variance
Guide to undertaking a repeated measures (within-subjects) analysis of variance in R.
Guide to undertaking the Friedman test in R.
Guide to constructing scatterplots in R.
How to calculate a correlation coefficient between two variables in R.
How to undertake a simple linear regression in R.
How to undertake a multiple linear regression, including checking model fit and reporting the results in R.
Multiple linear regression: Outliers, Durbin-Watson statistic and interactions in regression
A guide to detecting outliers, the Durbin-Watson statistic and interactions in regression in R.
How to undertake a binary logistic regression in R.
How to undertake a poisson regression in R.
How to undertake a time series analysis in R.
Multidimensional scaling analysis
How to undertake multidimensional scaling analysis in R.
How to undertake a principal components analysis in R.
How to undertake a power analysis to calculate the required sample size in R.
How to undertake a meta-analysis including drawing a forest plot in R
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