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Using the data set from problem 2.2, generate several plots: (a) Showing heart rate (HR) on the x-axis and systolic blood pressure (SBP) on the y-axis. Select a plotting symbol of your choice and use either PROC PLOT or PROC GPLOT. (b) A plot of diastolic blood pressure on the x-axis and systolic blood pressure […]

You have raw data consisting of ID (character), GENDER (numeric: 1 = Male,2 = Female), SES (character: L = Low, M = Medium, H = High), DRUG (character: A-H), and AGE (numeric). First create three formats, One for GENDER, one for SES, and one to group ages into three groups: <= 20,=”” 21-40,=”” and=”” 41=””

Suppose we have a variable called GROUP that has numeric values of 1,2, or 3. Group 1 is a control group, group 2 is given aspirin, and group 3 is given ibuprofen. Create a format to be assigned to the GROUP variable.

You have completed an experiment and have recorded a subject ID and value for variable A, B, and C. You want to compute means for A. B. and C but unfortunately. Your lab technician, who didn’t know SAS programming, arranged the data like this:

Run the following program to create a SAS data set called DEMOG: We want to recode WEIGHT and HEIGHT as follows (assume that WEIGHT and HEIGHT are integer values only): We then want to generate a table of WEIGHT categories (rows) by HEIGHT categories (columns). Recode these variables in two ways: (1) with “Il” statements;

Run the following program to create a temporary SAS data set called BLOOD. Produce frequencies for WBCs (white blood cell counts) using the following cutoffs: For WBC. Low = 3,000 to 4,000; Medium = 4,001 to 6,000; High = 6,001 to 12,000. Values below 3,000 (but not missing) are to be labeled ‘Abnormally Low’, and

A survey is conducted and data are collected and coded. The data layout is shown here: Collected data are shown next: (a) Create a SAS data set, complete with labels and formats for this questionnaire. (b) Generate frequency counts for the variables GENDER, PARTY, VOTE, FOREIGN, and SPEND. (c) Test if there is a relationship

A case-control study relating leukemia to exposure to non-ionizing radiation resulted in the following: In the cases (those with leukemia), there were 50 exposed and 500 non-exposed; for the controls, there were 40 exposed and 500 non-exposed. Write the necessary SAS statements to compute the odds ratio for non-ionizing radiation exposure. Make sure you have

You have a SAS data set called CASE_CONTROL in your CIMYDATA folder (or any other folder of your choice, or even a temporary data set). Variables are: EXPOSURE (character. values of l-yes, and 2-no), and OUTCOME (values of ‘l-dead. 2-ahve). Write a program to output a 2 X 2 table along with chi-square and the

A school administrator believes that larger class sizes lead to more discipline problems. Four class sizes (small, medium, large, and gigantic) are tested. The following table summarizes the problems recorded for each of the class sizes. Treating class size as an ordinal variable, test if there is a linear increase in the proportion of class