6.3.2 Changing labels and making a journal-ready figure.6.3.1 The ggplot2 layer metaphor for graphing data.6.2 Simulating, analyzing, and graphing the results from a 2x4 within-subjects design.5.13.1 Single factor design with a within-subjects factor.5.12 Running a between subjects ANOVA for a 2x2 Factorial design.5.11.1 Prettier results using kable and broom.5.11 Running an ANOVA for a single-factor design between-subjects design.5.8.3 Monte-Carlo One-way Repeated Measures Simulation.5.8.2 Monte-Carlo paired T-test Simulation.5.8.1 Monte-Carlo one-sample T-test Simulation.5.8 Power analysis and sample-size planning by Monte Carlo simulation.5.7.3 2x2 mixed design (1 within, 1 between).5.7 Simulating data for multi-factor designs.5.6.3 Mixed design ANOVAs with between and within factors.5.6.2 Within subjects ANOVA formulas (all factors within).5.6 Using the aov function for within or between-subjects designs.5.5.2 Simulating data for a one-way between subjects design with 3 levels.5.5.1 Simulating data for a one-way within subjects ANOVA with 3 levels.5.5 Single Factor ANOVAs: Data-Simulation and Analysis.5.4 Formatting data in R for more complex designs.5.3.4 Generality of the t-test examples.5.3.3 Simulating a paired samples t-test (two conditions, within-subjects).5.3.2 Simulating an independent samples t-test (two groups, between-subjects).5.3 t-test:Data Simulation and Analysis.5.1.2 Sampling from a normal distribution.5.1.1 Sampling random numbers (uniform distribution).4.1.3 Practical issues with data in Psychology.3.2 Use Hypothesis to annotate your solutions.3 Programming Challenges I: Learning the fundamentals.2.3.7 Arrays, Lists, Dataframes, Factors and other classes.1.4 What is the computer actually doing? A view from the top.1.3 Foundational concepts in computer programming.1.2.4 Applying the tools to the problems you want to solve.1.2.3 Understanding the tools available to you.1.1 Why should Psychologists learn to program?.1 Fundamentals of Computer Programming Languages.