Chapter 2 introduces the idea that business statistics should be extrapolated to practical outcomes wherever possible, especially in the business context. Typically, extrapolation means that you take the results of a statistical analysis, combine the statistical results with other information like financial data, and consider further implications of your statistics that are not immediately apparent in the initial analyses.

Because this is a business book first and foremost, I concentrate on extrapolation of statistical measurements to financial profitability. While there are many things to which you could extrapolate, financial values are one of the most valuable in the business context. No matter what you are measuring – operational production, customer loyalty, employee turnover, negotiation outcomes, and many others – you can often determine the financial value underlying these variables.

For instance, a company may do marketing research that shows a link between a promotional campaign and purchasing behavior among customers. However, once such a statistical link has been shown, the analyst can go one step further to show that the financial (revenue) value of any improved purchases is worth the cost of the promotional campaign.

Extrapolation does extend beyond financial variables of course. For instance, research on organizational hiring practices could be used to extrapolate the impact of change in such practices on unemployment rates. You can extend the principles taught in this chapter that are focused on financial analysis to other types of final outcomes.

This chapter undertakes an introduction to doing financial analysis based on statistics, covering the core principles and giving a simple example based on averages.