Skip to main content
\(\newcommand{\identity}{\mathrm{id}} \newcommand{\notdivide}{{\not{\mid}}} \newcommand{\notsubset}{\not\subset} \newcommand{\lcm}{\operatorname{lcm}} \newcommand{\gf}{\operatorname{GF}} \newcommand{\inn}{\operatorname{Inn}} \newcommand{\aut}{\operatorname{Aut}} \newcommand{\Hom}{\operatorname{Hom}} \newcommand{\cis}{\operatorname{cis}} \newcommand{\chr}{\operatorname{char}} \newcommand{\Null}{\operatorname{Null}} \newcommand{\lt}{<} \newcommand{\gt}{>} \newcommand{\amp}{&} \)

Chapter1Sizing the Market

The first task in any data-driven decision process is to make sense of your data. In the Market It! project, you have a limited set of data that was gathered by your marketing division from a collection of "test markets," each of which is a representative sample of the entire national market for your product. However, the test markets each have different sizes and were tested at different price points. Your first task therefore is as follows:

The key quantitative reasoning strategy for this decision involves no calculus and little algebra; instead, it is an instance of proportional reasoning. Mathematically, the same strategy you might use to scale up a cookie recipe to feed a crowd is the strategy you'll use to scale up the demand in each test market to predict demand in the nationwide market for your product.