In the Purchase Orders database, conduct a Pareto analysis of the cost per order data. What conclusions can you reach?

Data Analytics by Geoffrey
  1. The Excel file MBA Motivation and Salary Expecta-tions provides data on students’ pre-MBA salary and post-MBA salary expectations. Define range names for each of these ranges and then use the range names in formulas to find the expected salary increase for each of the respondents.
  2. The Excel file Syringe Samples provides data for 15 samples of an important measurement in the manu-facturing process for medical syringes. Define range names for each of the samples and then use these range names in formulas to find the average value for each sample.
  3. The Budget Forecasting database shows estimated expenses for the last nine months of the coming year. Define range names for each month and type of expense and use the range names in formulas to find the total for each month and type of expense.Data Queries: Tables, Sorting, and Filtering
  4. Convert the Store and Regional Sales database to an Excel table. Use the techniques described in

Example 2.4 to find:

  1. the total number of units sold.
  2. the total number of units sold in the South region.
  3. the total number of units sold in December.

 

  1. Convert the Purchase Orders database to an Excel

table. Use the techniques described in Example 2.4

to find:

  1. the total cost of all orders.
  2. the total quantity of airframe fasteners purchased.
  3. the total cost of all orders placed with Manley Valve.

 

  1. The Excel file Economic Poll provides some demo-graphic and opinion data on wheton whether the economy is moving in the right direction. Convert these datainto an Excel table and filter the respondents who are homeowners and perceive that the economy is not moving in the right direction. What is the distribution of their political party affiliations?
  1. The Excel file Corporate Default Database sum-marizes financial information for 32 companies and their perceived risk of default. Convert these data into an Excel table. Use table-based calculations to find the average credit score, average debt, and average equity for companies with a risk of default, and also for those without a risk of default. Does there appear to be a difference between companies with and with-out a risk of default?
  2. Open the Excel file Store and Regional Sales Data-base. Sort the data by units sold, high to low.
  3. In the Excel file Automobile Quality, search for and add a new column for the country of origin for each brand. Then sort the data from the lowest to highest by number of problems per 100 vehicles using the sort capability in Excel. What conclusions can you reach?
  4. In the Purchase Orders database, conduct a Pareto analysis of the cost per order data. What conclusions can you reach?