CSUG Clustering Cars Project

*Will give you my SAS school login!

According to Federal Reserve Bank of St. Louis, “The unemployment rate represents the number of unemployed as a percentage of the labor force. Labor force data are restricted to people 16 years of age and older, who currently reside in 1 of the 50 states or the District of Columbia, who do not reside in institutions (e.g., penal and mental facilities, homes for the aged), and who are not on active duty in the Armed Forces.”

The dataset called UNRATE.xls (Links to an external site.) contains monthly unemployment rate in U.S. from 1948 to 2019. Using this dataset, perform exploratory analysis using SAS.

1. First, upload the dataset into SAS Studio.
2. Provide the summary statistics of the dataset. Explain the characteristics of the dataset.
3. Under Tasks and Utilities in SAS Studio, select Graph Series Plot. Then, create a series plot of unemployment rate where observation-date is the X axis and unemployment rate is the Y axis. Describe the pattern you see from the graph.
4. Write the SAS code that divides the dataset into four groups: (i) 1948 to 1969; (ii) 1970 to 1984; (iii) 1985 to 2007; and (iv) 2008 to 2019. Then, create a series plot of unemployment rate for each group. Describe the pattern you see from each graph. Include your SAS code in the Word document for submission.

Take the screenshots of the SAS output and include them into a Word document along with your explanations. Make sure that each SAS output shows the system date and this can be done using the following code:

data _null_;
call symput ('timenow',put (time(),time.));
call symput ('datenow',put (date(),date9.));
run;

title "The current time is timenow and the date is datenow";
proc print data=sashelp.buy;
run;

Include all the screenshots and your answers in a Word document and submit the document to Canvas for grading. Clearly label all the SAS codes and outputs. In addition, provide a short description of any challenge(s) you faced during this assignment.

Your submission should be two to three pages in length and conform to the CSU Global Writing Center (Links to an external site.). Review the grading rubric to see how you will be graded for this assignment.

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In this assignment, assume that you work in an automobile industry to examine different makes and models of automobiles. Your company is particularly interested in clustering of the variables so that they can determine if the data are suitable for use in the next phase of their upcoming analytics project. Complete the following tasks:

1. Locate the data from Libraries My Libraries SASHELP CARS.
2. Using correlations and scatterplots, examine the linear relationships among the quantitative variables: MSRP, Invoice, EngineSize, Cylinder, Horsepower, MPG_City, MPG_Highway, Weight, Wheelbase, and Length. Comment on the relationships.
3. Provide the summary statistics for all quantitative variables using Origin as a classification variable. Comment on the summary statistics. What are some of the key characteristics from the data?
4. Provide a graphical summary (such as histogram) for all quantitative variables using Origin as a classification variable. Comment on the graphs.
5. Using the whole dataset based on quantitative variables, conduct the cluster analysis using either PROC FASTCLUS or PROC VARCLUS or both. Make sure to interpret the SAS output.
6. Repeat part 5 using the variable Origin as a classification (group) variable.

Note: PROC FASTCLUS is based on k-means procedure. More information including description, syntax, and examples can be found from the website: SAS FASTCLUS (Links to an external site.)

PROC VARCLUS is based on linear combinations of the variables in the cluster. More information including description, syntax, and examples can be found from the website: SAS VARCLUS (Links to an external site.)

For each part, take the screenshots of relevant SAS output and paste them into a Word document. Include all relevant calculations and your answers to all assignment items and submit the document to Canvas for grading. Clearly label all elements in your submission. In addition, provide a short description of any challenge(s) you faced during this assignment.

Your submission should be three to four pages in length and conform to the CSU Global Writing Center (Links to an external site.). Review the grading rubric to see how you will be graded for this assignment.