ECO $230$ PRACTICUM SPRING $2024$

This prompt is for the Practicum portion of your final exam. Please review it carefully before you begin the exam.

The scenario and data description are included here. You will receive the actual data when you launch the exam.

This exercise is open note, book etc, but is not a team exercise. You must complete your work without

communicating with others. However, you are welcome to discuss the prompt and your strategy with others before

you and they attempt the exam. The rubric does include points for originality of work.

SCENARIO

An unsecured personal loan is a fixed$-$rate loan that is not backed by collateral and is repaid in monthly

installments over a specific term, usually two to seven years. When you need money to cover a large expense or to

consolidate your debt, consider a personal loan. You can use the funds for almost any purpose.

Using loan data from across the United States, your consulting firm has been tasked with analyzing loans issued

before $2018.$ Your team has decided to address the following questions in your report:

$$ Are loans equally distributed across reasons or do some reasons have more loans than others?

$$ Which loan term is likely to have a higher loan amount on average?

$$ Was the average interest rate per loan lower than the national average of $10\mathrm{.}32\%?$

$$ More risky loans generally have higher interest rates and monthly payments. Is that true in this data set?

$($Note: You can just address interest rates or monthly payments, you are not required to do both if you

answer this question$)$

DATA DESCRIPTION

The data grouping is cross$-$sectional. The unit of analysis is one observation per loan.

The variables are:

$$ loanID: loan identification number

$$ amount: loan amount in dollars

$$ term: loan term is $36$ or $60$ months

$$ rate: interest rate as a decimal

$$ payment: monthly payment amount

$$ grade: grade of loan: A is least risk; G is most risk

$$ status: loan status: DEFAULT, CURRENT, CHARGED OFF, etc

$$ reason: applicants$$ purpose of the loan

$$ state: two letter state code of applicant

REQUIREMENTS

Using Excel, Tableau and RStudio, please conduct preliminary analysis of any of the questions above. Your analysis

should include:

$$ At least one graph

$$ At least one table $($e$.$g$.$ pivot table$)$

$$ At least one hypothesis test

$$ A brief bullet point summary of your findings

$$ Work in RStudio, Tableau, and Excel

You do not need to address all questions in the prompt. You may choose to focus on only one if you like.

SUBMITTING COMPLETED WORK

Upload your Excel workbook, your Tableau Packaged Workbook, and your knit RMarkdown pdf to Canvas.

BONUS

For five extra points, replicate in R a piece of your analysis from Excel or Tableau. For example, create a table in R

that matches what you found with an Excel pivot table or make a visual in R that matches something made in

Tableau. Alternatively, you can produce in R something different than what you are submitting from Excel or

Tableau. In short$-$ if you want to receive the bonus points for use of R$,$ you must produce something relevant to

the prompt that is NOT a statistical test.

FORMAL GRADING CRITERIA

Yes No

Does the work include at least one graph, one table, and one hypothesis

test?

Continue

grading

$0/30$

Are the interpretations of the output provided in bullet points generally

correct?

Continue

grading

$5/30$

Is the graph appropriate for the type of data analyzed? Continue

grading

$10/30$

Is the statistical test used appropriate for the type of data analyzed? Continue

Grading

$15/30$

Rating Points

Extent to which the work follows data visualization best practices $1-3$

Extent to which the organization of Excel Workbook follows best practices $1-3$

Extent to which the organization and annotations of R code follow best

practices

$1-3$

Extent to which interpretation$($s$)$ of statistical test$($s$)$ are clear and correct $1-3$

Originality of the approach $1-3$