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6.4: Correcting for Other Factors

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    Often we are interested in plotting data where the variable of interest is affected by other factors than the one we are interested in. For example, let’s say that we want to understand how the price of gasoline has changed over time. Figure 6.13 shows historical gas price data, plotted either with or without adjustment for inflation. Whereas the unadjusted data show a huge increase, the adjusted data show that this is mostly just reflective of inflation. Other examples where one needs to adjust data for other factors include population size (as we saw in the crime rate examples in an earlier chapter) and data collected across different seasons.

    Figure 6.13: The price of gasoline in the US from 1930 to 201 (obtained from with or without correction for inflation (based on Consumer Price Index).

    This page titled 6.4: Correcting for Other Factors is shared under a not declared license and was authored, remixed, and/or curated by Russell A. Poldrack via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.