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Go over the motivational cases included in Chapter 1 (Introduction).
Confirm that you have installed R/RStudio. You should be able to download and load in RStudio as shown in Chapter 1.
Then, complete the following examples.
Load in the long-format SOCR Parkinson’s Disease data and export it as wide format. You can only select any 5 variables (not all), but note that there are several time observations for each subject. You can try using the reshape()
method or tidyverse techniques.
Create a Data Frame storing the SOCR Parkinson’s Disease data and call summary()
and Hmsc::describe()
to summarize some of the feature characteristics.
Using the same SOCR Parkinson’s Disease data:
L_caudate_ComputeArea<600
.L_caudate_Volume
.Gender
and Age
.Age
and the correlation between Age
and Weight
.R_fusiform_gyrus_Volume
and scatterplot L_fusiform_gyrus_Volume
and R_fusiform_gyrus_Volume
.Note: You don’t have to apply these data filters sequentially, but this can also be done for deeper stratification.
Generate \(1,000\) standard normal variables and \(1,200\) Cauchy distributed random variables and generate a quantile-quantile (Q-Q) probability plot of the pair of samples.
Generate an R
function that given an object (e.g., vector, matrix, array, tensor), it computes the arithmetic average and compare it against the mean()
function.