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This Excel project asks you to use the skills you’ve learned in Excel I, Excel II, and Excel comprehensive practice to answer the following question. For this project, you will need the following files:

  1. No41,51,61,71.txt: this file contains the quarterly revenue data for company XYZ.
  2. Main file.xlsx: this file contains three macro-economic variables, disposable income in billions of dollars, unemployment rate in percentage and work force population in thousands.

Data contained in these two files are different from those you used for the data analysis project. You should only use these two files.

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  1. Import the company revenue data in file No 41, 51. 61. 71.txt to a new worksheet in Main file differently. Rename the worksheet Company revenue. On the new worksheet Company revenue, perform the following tasks.
  2. Insert a new column to the right of the first column and name the new column ‘Quarter’ in B1. In the rest of the cells in column B, use a formula to fill in the quarter of the date such that if the month of the date is 3, enter “1”; if the month is 6, enter “2”; month 9, enter “3”; and month 12, enter “4”.
  3. This step asks you to combine the data on the four worksheets together. On the Company revenueworksheet, use your choice of Excel function to bring the data on the Disposable IncomeUnemployment rate and Population worksheets to create a comprehensive data worksheet that contains the following columns: Quarter, Date, Revenue, Disposable Income, Unemployment rate, and Population.

Note that the dates are different across the four worksheets and certain dates in the revenue data are deleted on purpose. What you have done in the data analysis by simply copying and pasting will not work. You must use Excel functions to finish the task; manually matching does not count.

  1. Use the comprehensive data sheet you just created and do the following.
  2. Delete observations with invalid data for any of the variables (i.e, where you see ‘#N/A’). The best way to do so is to first sort the data by revenue, then all observations with invalid data will be clustered at the bottom of the file. Delete all the rows with ‘#N/A’ for revenue, even if data are available for other variables. Then do the same sorting for unemployment rate in case there are any other invalid data.
  3. Sort the data in ascending order by date.
  4. In Column G, which should be an empty column, do the following:
  • Name the column ‘Income growth’ in cell G1
  • Starting from G3, calculate the growth rate of Disposable Income using the formula below

(Current period income-previous period income)/previous period income

  • Paste special values so that the data in Column G are numbers not formulas.
  • Format the values in Column G to show a percentage with two decimal places.
  • In cell H2, use a formula to calculate the average growth rate of disposable come.
  1. Freeze the first column so that Column A (Date) is always shown.
  2. Run a multiple linear regression using Revenue as the dependent variables and using Unemployment rate and Population as the independent variables.
  • Show the results in a new worksheet.
  • Highlight the variables that are significant.
  • A formal regression is required. A scatter plot with regression equation doesn’t count.

Special notes: 1. Do not eliminate the active formulas used unless otherwise required. 2 You can use other formulas than the those specified in the instruction as long as you can achieve the same results