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I'd like to run a regression analysis but I am not sure if what I am trying to do makes sense.

My dependent variable is the total spending of a customer and my independent variables are the number of products bought that are equal to or higher than 10 USD and the number of products bought that are less than 10 USD.

I am trying to understand whether customers who buy more expensive products spend more money overall or not.

I am not even sure if this is a regression problem tho. So if you have any other suggestions on how I should approach this problem, please let me know!

Thanks,

update: would it make sense to look at the correlation between # of products >= 10 USD and total spending vs # of products < 10 USD and total spending? so the first one's correlation coeff is 0.87 and the second one's correlation coeff is 0.38.

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If you want to use regression on this, one possible way to do it would be to normalise both "number of products" variables and then fit for example a linear model. You can then assess the relative importance of the 2 variables for predicting the "total spend" variable.

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  • $\begingroup$ Thank you, Dave, for your answer. So you say that it's technically OK to use these "# of products" variables as independent variables in this case? $\endgroup$
    – Fenchurch
    Commented Jun 12, 2019 at 19:56
  • $\begingroup$ Yes, as long as what you mean by independent is, that they're the "independent" variables in the sense that the "total spend" variable is "dependent" because you're regressing it on the other 2. Not in the sense of "statistically independent". $\endgroup$
    – Dave
    Commented Jun 12, 2019 at 22:26

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