# 1 Basics

## 1.2 R/RStudio Installation

Confirm that you have installed R/RStudio. You should be able to download and load in RStudio as shown in Chapter 1.

# 2 Problems

Then, complete the following examples.

## 2.1 Long-to-Wide Data format translation

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.

## 2.2 Data Frames

Create a Data Frame storing the SOCR Parkinson’s Disease data and call summary() and Hmsc::describe() to summarize some of the feature characteristics.

## 2.3 Data stratification

Using the same SOCR Parkinson’s Disease data:

• Extract the first 10 subjects.
• Find the cases for which L_caudate_ComputeArea<600.
• Sort the subjects based on L_caudate_Volume.
• Generate frequency and probability tables for Gender and Age.
• Compute the mean Age and the correlation between Age and Weight.
• Plot Histogram and density of 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.

## 2.4 Simulation

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.

## 2.5 Programming

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.

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