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Getting old and rich

As a business analyst asked to examine user profiles, you started by getting descriptive stats. Next, you plotted frequencies and scatterplots to learn about important relationships.

Going a level deeper, you now want to calculate the exact relationship between age and income. Explicitly calculating the incremental relation between these important matching variables will help the marketers in your company complete user personas and gain a specific picture of many of the profile attributes.

In review, the CORREL() function accepts an X column and a Y column for comparison. In our analysis, x = age and y = income.

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  • In F2, find the correlation between income and age.
  • Calculate a best fit line with LINEST() in cell G2 for income and age.
  • In cell E2, calculate the "fit" of the linest function using "intercept" + ("age" * "slope") referring to the appropriate cells.

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