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You should be able to download and load in RStudio the Foundations of R code. Then run all the examples.
You have learned wide-to-long in lecture notes. Now, let’s explore wide-to-long. Load in the long-format SOCR Parkinson’s Disease data and export it as wide format. You can use only 3 variables(exclude case
and time variable) you select. Please note that there are several time observations for each subject. You need transform according time variable. Try to use reshape
function.
Create a Data Frame of the SOCR Parkinson’s Disease data and compute a summary of 3 features you select.
Using the same SOCR Parkinson’s Disease data and extract rows satisfying Time=0
. Then:
L_caudate_ComputeArea
<600.L_caudate_Volume
in descending and ascending order.Age
and Sex
.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 student t
distributed random variables with df=20
and generate a quantile-quantile (Q-Q) probability plot of the 2 samples. Then, compare it with qqnorm
of student t
simulation.
Generate a function that computes the arithmetic average and compare it against the mean
function using the simulation data you generate in the last question.