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Story Name: Forbes 500 Companies Sales
Story Topics: Economics 
Datafile Name: Companies
Methods: ANCOVA , Transformation 
Abstract: This dataset holds several facts about 77 companies selected from the Forbes 500 list for 1986. This is a 1/10 systematic sample from the alphabetical list of companies. The Forbes 500 includes all companies in the top 500 on any of the criteria, and thus has almost 800 companies in the list. Companies are often interested in how to increase sales. This dataset lends itself to several analyses, but only a simple ANCOVA is discussed here.

 Many of the variables are skewed -- a common occurrance with financial data -- which suggests that much of the data are better analyzed after taking logarithms. For this model one should take the log of Sales and Assets.

 A scatterplot of log(Sales) vs log(Assets) shows a general linear trend. Separating each market sector shows that each sector follows the overall trend, but at different levels -- a good example of a simple Analysis of Covariance.

 An ANCOVA of Log(Sales) predicted by Log(Assets) as a covariate and Sector as a discrete factor works well for these data.

Image: Scatterplot of log(Sales) vs. log(Assets) colored by Sector.

Reference: Forbes, 1986
Authorization: free use
Description: Facts about companies selected from the Forbes 500 list for 1986. This is a 1/10 systematic sample from the alphabetical list of companies. The Forbes 500 includes all companies in the top 500 on any of the criteria, and thus has almost 800 companies in the list.
Number of cases: 77
Variable Names:
  1. Company: Company Name
  2. Assets: Amount of assets (in millions)
  3. Sales: Amount of sales (in millions)
  4. Market_Value: Market Value of the company (in millions)
  5. Profits: Profits (in millions)
  6. Cash_Flow: Cash Flow (in millions)
  7. Employees: Number of employees (in thousands)
  8. Sector: Type of market the company is associated with