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lm()
The lm() function fits a linear model to data. Example 1: # fits an empty model lm(Thumb ~ NULL, data = Fingers) Example of output from running the code above: Example 2: # fits a model with one explanatory variable lm(Thumb ~ Sex, data = Fingers) ...
gf_bar()
The gf_bar() function creates a bar graph. It can be used to visualize the distribution of a categorical variable by counting the number of observations for each group of the category. Bar graphs can also be used with the gf_facet_grid() function. ...
gf_density()
The gf_density() function will overlay a density plot onto a density histogram (i.e., gf_dhistogram(), not gf_histogram()). The density plot is a smoothed out version of the distribution. They can be helpful when you want to get a better idea of the ...
gf_histogram()
The gf_histogram() function will create a frequency histogram for a quantitative variable. This means it will show the number of cases observed in the data for each value of the variable. (See gf_dhistogram() for information on density histograms). ...
gf_labs()
The gf_labs() function can be used to modify the labels of your plots. You can add a title for your plot, or modify the label for the x- or y-axis. Example: # Add a title and change the label for the x-axis gf_histogram(~Thumb, data = Fingers) %>% ...