Essentially ‘One-way independent ANOVA’ but taught using a general linear model framework. Centring variables (grand mean centring), specifying interaction terms, moderation analysis, simple slopes analysis, Johnson-Neyman intervals, mediation with one predictor, direct and indirect effects, mediation using lavaan. Comparing two independent means, comparing two related means, effect sizes. discovr_09: Categorical predictors with two categories (comparing two means).Viewing model parameters with broom, model parameters, standard errors, confidence intervals, fit statistics, significance. Visualizing the data, fitting GLMs with one and two predictors. discovr_08: The general linear model (GLM).Pearson’s r, Spearman’s Rho, Kendall’s tau, robust correlations. Grouping summary statistics by multiple categorical/grouping variables. Calculating skewness, kurtosis and the number of valid cases. Calculating z-scores (standardizing scores). Spotting outliers using histograms and boxplots. Restructuring data from messy to tidy format (and back). The ggplot2 package, boxplots, plotting means, violin plots, scatterplots, grouping by colour, grouping using facets, adjusting scales, adjusting positions." , adding confidence intervals to data summaries. discovr_03: Confidence intervals: interactive app demonstrating what a confidence interval is, computing normal and bootstrap confidence intervals using.discovr_02: Summarizing data (frequency distributions, grouped frequency distributions, relative frequencies, histograms, mean, median, variance, standard deviation, interquartile range).(functions and objects, packages and functions, style, data types, tidyverse, tibbles) Given the current global situation and the fact that lots of instructors are needing to teach remotely I’m making what I have available before the book is finished and will update as and when new tutorials are written. Some longer chapters have several tutorials that break the content into more manageable chunks. For example, discovr_04 would be a good tutorial to run alongside teaching related to chapter 4, and so on. The tutorials are named to correspond (roughly) to the relevant chapter of the book. Getting started with R and RStudio interactive tutorial.RStudio by completing this tutorial (includes videos): RStudio adds functionality that make working withĮasier, more efficient, and generally more pleasant than working in RStudio is a user interface through which to use R is a free software environment for statistical analysis and graphics. Then you probably already know what it is. related) and offered to support tutors and students using my textbook. The discovr package is free (as are all things Once a tutorial is running it’s a bit like reading excerpts of the book but with places where you can practice the R code that you have just been taught. The tutorials are written using a package called
It will include all datasets, but most important it will contain a series of interactive tutorials that teachĪlongside the chapters of the book. The discovr package will contain tutorials associated with my textbookĭiscovering Statistics using R and RStudio, due out in early 2021.
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