- #DATA ANALYSIS TOOLPAK EXCEL 2011 DOWNLOAD HOW TO#
- #DATA ANALYSIS TOOLPAK EXCEL 2011 DOWNLOAD DOWNLOAD#
#DATA ANALYSIS TOOLPAK EXCEL 2011 DOWNLOAD HOW TO#
Following are examples of how to transform four of the variables: Loan Status: This is the variable we're using as our dependent variable, but currently it is non-numeric data. Unless the analysis is done exclusively using categorical data, transform the data into a numeric variable. Transform the non-numeric data into numeric data. For example, we would predict a negative relationship between "dti" (the debt-to-income ratio) and loan repayment because the more debt you have, the less likely you'll be able to repay a loan. Using the data analysis toolpak, predict how the independent variables might relate to the loan repayment. Deliverable 2: In the second section of your report (after Deliverable 1), prepare a descriptive analysis titled "Descriptives" that includes a screenshot of descriptive statistics for all the proposed dependent and independent variables. Using the data analysis toolpak (Excel: Data>Analysis>Data Analysis>Descriptive Statistics), run a descriptive analysis for your proposed independent and dependent variables looking at the minimums, maximums, and averages (see Chapter 6) or generate a histogram to identify unusual outliers or anomalies (see Chapter 7) to assess whether there are any errors. Make sure there are no errors in the data. Hint: Run the COUNT() function in Excel to see if the count of each variable equals the count of loans in the dataset, etc. Check the dataset to make sure that all variables are complete and are not missing data. Step 2 After determining the variables to use in the analysis, make sure the data is as follows. Next, within the document, identify and type the names of the dependent variable and at least five proposed independent variables that you think explain loan repayment. Title the first section of the document “Dependent and Independent Variables". As the data analyst on this project, it is your job to find potential independent variables that may help explain loan repayment.ĭeliverable 1: Once you have found all variables that may explain loan repayment, prepare a document (in Microsoft Word), and save it as "Project 1: Lending Club Loan Analysis First Name and Last Name" (inserting your first and last name). Length of loan ("term", Column F), whether the income is verified (verification_status, Column O), or state where they live ("addr_state" in Column X) are also possible independent variables. Perhaps the debt-to-income ratio might determine if the borrowers (“dti” in Column Y) will be able to repay the loan. For example, loan repayment might be determined by whether a borrower owns her home, rents her home, or still has a mortgage from the information contained in Column M, labeled "home_ownership." Perhaps length of employment matters ("emp_length” in Column L) or amount of annual income ("annual_inc" in Column N) will help determine repayment. That is, which variables are most likely to explain whether the loan was repaid or not? In this case, you may want to examine how much debt the borrower already has or how much income he or she has available to pay back loans, etc. Potential Independent or Explanatory Variables The first step in determining the best data for use is to consider the various explanatory, or independent, variables. Later in the analysis, we will transform this variable into “Loan Paid," which will then serve as our primary dependent variable. Dependent Variables In column Q, titled "loan_status," there are two possible entries, "Charged Off" or "Fully Paid." This is the dependent variable we are examining. For example, Column D-funded_amnt"-lists the amount of each loan that was funded. Each column represents an attribute of the loan or of the borrower of that loan. Open the file named "LoanStats3a.csv" in Excel and look at the data. We don't have to wait for time to pass to see the ultimate resolution of the loan repayment. One reason we use data that is so "old" in our analysis is that the loan repayment will be either completed or it will be charged off (not repaid) by today's date.
#DATA ANALYSIS TOOLPAK EXCEL 2011 DOWNLOAD DOWNLOAD#
Step 1 Download the file named "LoanStats 3a.csv" from Connect, which covers the loan data from 2007 - 2011. Lending Club provides a summary dataset of the loans extended to borrowers since 2007.
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