Description

Note: For each question, produce separate PDF files for SAS code and output. Those PDF files should be uploaded to the Crowdmark under each question.

Q1) Use the provided FISH data set and do the followings.
a) Sort the data by lake type and dam status (LT and DAM). You won’t need the latitude or longitude variables for this assignment, so you can drop them.
b) Use PROC MEANS to calculate the mean and median for each of the remaining numeric variables (all nine of them) separately for each combination of LT and DAM. Use ODS to save the results to a data set named STATZ that keeps only the necessary variables.
c) Combine these summary statistics with the original dataset (FISH) using an appropriate join technique to create a data set named ALL.
d) After the data sets are joined, but in the same data step, do the following. You must use arrays to get credit for this portion of the assignment.
▪ Difference from the mean [variable – mean.of.variable]
▪ Percent difference from the mean [(variable – mean.of.variable)/mean.of.variable]
▪ Difference from the median [variable – median.of.variable]
▪ Percent difference from the median [(variable – median.of.variable)/median.of.variable]
• Apply reasonable formats and labels to all the variables that weren’t originally in the FISH data set.
• Drop any irrelevant variables.
e) Sort your ALL data set by NAME.

Create Frequency Reports using SAS dataset called ‘sanfran’ as follows.

a) Use PROC FREQ to create a report using the sanfran data set that displays the frequency count for each Destinatation, and a separate frequency count for each DepartDay. Add an appropriate title to each frequency table.
b) Modify the program from part ‘a’ above to repeat the frequency tables, but without the cumulative frequencies.
c) Use PROC FREQ to create a two-way frequency table using the sanfran data set that displays the frequency count for each Destination by DepartDay combination.

a) Validating Data with PROC FREQ: PROC FREQ is useful in checking the validity and completeness of data (i.e., invalid values stand out). Use PROC FREQ to check the validity of the variables Gender and JobCode in the mechanics data set.
i. What do you notice about the values of the variable Gender? (Comment)
ii. What do you notice about the values of the variable JobCode? (Comment)
Modify the previous report to display the frequency count for each Gender by JobCode. What are the JobCode values for the invalid values of Gender?
b) Creating Basic Summary Reports:
i. Generate a PROC MEANS report using the sanfran data set as input to display statistics for the variables CargoRev and TotPassCap only. Remove any titles currently in effect.
ii. Modify the previous report to display the data for each Destination. Include the following statistics (number of observations, mean, median, mode, range and standard deviation. Limit all output to two decimal places.

a) Datasets ONE and TWO are shown here. Use PROC SQL to create a new, temporary SAS data set (Both) containing Subj, Height, Weight, and Salary. Do these three ways: first, include only those subjects who are in both data sets, second, include all subjects from both data sets, and third, include only those subjects who are in data set ONE.

Dataset ONE:

Subj Height Weight
001 68 155
002 75 20
003 65 99
005 79 266
006 70 190
009 61 122

Dataset TWO:

Subj Salary
001 $46,000
003 $67,900
004 $28,200
005 $98,202
006 $88,000
007 $57,200

b) Use PROC SQL to create a new temporary SAS data set (Percentages) from the Blood dataset (attached), containing the variables Subj, RBC, WBC, MeanRBC, MeanWBC, Percent_RBC, and Percent_WBC. The first few observations in the output shou look like this:

Mean Mean Percent_ Percent_ Subj RBC WBC RBC WBC RBC WBC

1 7.40 7710 5.884 6532.5 125.765 118.025
2 4.70 6560 5.884 6532.5 79.878 100.421
3 7.53 5690 5.884 6532.5 127.974 87.103 4 6.85 6680 5.884 6532.5 116.417 102.258 5 7.72 . 5.884 6532.5 131.203 .