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SAS: In-Class Activity 6
For this activity, you’ll create a SAS program. There is no need to upload it. This is a chance for you to practice with your instructor (and other students) present to obtain help.
Notes:
Although we aren’t turning this in, you should use good programming practices (see SAS File Submission Guidelines).
Include a header with your name and the purpose of the file.
Provide comments throughout the program explaining the upcoming code’s purpose.
Use spacing and indentation to improve readability.
The goal of this activity is to practice with numeric summaries.
The dataset for this activity has information about student performance and possible related factors. The dataset is available via the URL:
https://www4.stat.ncsu.edu/~online/datasets/StudentData.txt
The StudentData.txt data comes from the UCI machine learning repository. Information about the variables in the dataset is available at this link
.
Programming questions
Write (or copy from below) code corresponding to each question below. Note: We read in this data set in ICA 5 so you can just set up the library and the data set should already be there! That means you can likely skip step 2.
1.
Create a permanent library using a LIBNAME statement.
2.
(Optional) Create code to import the StudentData.txt file from the URL above into your permanent library created in question 1. Note: This is a ‘;’
delimited file. 3.
Run the following code (altering the names corresponding to the library and dataset) to make sure the g1 and g2 variables are stored as numeric variables:
DATA yourlib.yourdataname;
SET yourlib.yourdataname;
numG1 = input(G1, 8.);
numG2 = input(G2, 8.);
RUN;
4.
Use a PROC to produce the following summary statistics about the age and
numG1 variables (and no other summary statistics):
Sample Mean
Sample Standard Deviation
Sample Maximum
5.
Use a PROC to produce the same summary statistics about the age and numG1 variables (and no other summary statistics) at every combination of the variables of the Mjob variable.
6.
Use PROC UNIVARIATE to produce summary statistics about the numG1 and numG2 variables at every combination of the Mjob variable.
7.
Use a PROC step to find the correlation between the age, numG1, and numG2 variables for every setting (or level) of the Mjob variable.
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