15.5.2 Transforming skewed variables prior to standard regression. 15.5.1 Adding a regression line to a plot. 15.5 Logistic regression with glm(family = "binomial". 15.4 Regression on non-Normal data with glm(). 15.3 Comparing regression models with anova(). 15.2.6 Getting an ANOVA from a regression model with aov(). 15.2.5 Center variables before computing interactions!. 15.2.4 Including interactions in models: y ~ x1 * x2. 15.2.3 Using predict() to predict new data from a model. 15.2.2 Getting model fits with fitted.values. 15.2.1 Estimating the value of diamonds with lm(). 14.7 Repeated measures ANOVA using the lme4 package. 14.6 Getting additional information from ANOVA objects. 14.5 Type I, Type II, and Type III ANOVAs. 14.1 Full-factorial between-subjects ANOVA. 13.5.1 Getting APA-style conclusions with the apa function. 13.1 A short introduction to hypothesis tests. 12.3.1 Complex plot layouts with layout(). 12.3 Arranging plots with par(mfrow) and layout(). 11.10 Test your R might! Purdy pictures. 11.8 Saving plots to a file with pdf(), jpeg() and png(). 11.7.5 Combining text and numbers with paste(). 10.6 Test your R might!: Mmmmm…caffeine. 9.6.3 Reading files directly from a web URL. 9.1.1 Why object and file management is so important. 8.7 Test your R might! Pirates and superheroes. 7.3.1 Ex: Fixing invalid responses to a Happiness survey. 
7.2.2 Counts and percentages from logical vectors.
6.2.3 Sample statistics from random samples.6.2.2 Additional numeric vector functions.4.4.4 Example: Pirates of The Caribbean.
#Graph r type code
4.3.1 Commenting code with the # (pound) sign. 4.3 A brief style guide: Commenting and spacing. 4.2.1 Send code from an source to the console. 1.5.2 Getting R help and inspiration online.
0 kommentar(er)
