Using the data set from problem 2.2, create a chart showing the sum of procedures (N_PROC) for each GENDER with the contribution of each value of RACE shown within each bar (please see following chart):

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:

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 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=””

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

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

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;

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 researcher wants to determine if soundproofing a classroom leads to better behavior among the students. In the standard classrooms, there were 30 behavioral problems from a total of 250 children. In the soundproofed classrooms, there were 20 behavioral problems from a total of 300 children. Test if room noise results in an increased number