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April 5th, 2017, 06:43 AM   #1
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What Type Of Regression Should I Do With This Data?

I have radio market populations. The difference in population between consecutive market numbers is bigger for bigger markets. Since the data is not linear, what type of regression should I do? My calculator can do these types of nonlinear regression:

Quadratic
Cubic
Quartic
Natural logarithm
Exponential
Power
Logistic
Sine
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April 5th, 2017, 09:15 AM   #2
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Plot the data on a scattergraph look at the shape and go from there
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April 5th, 2017, 03:26 PM   #3
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There are 274 numbers, and the difference between them is big enough that it wouldn't look nice on a scatterplot unless the y scale went up exponentially. One way to think about it is the salary of 274 employees, with the richest few bringing the mean way above the median.
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April 5th, 2017, 04:55 PM   #4
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Quote:
... unless the y scale went up exponentially
if the data set models an exponential function, then the data plot of x vs. log(y) would look linear
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April 6th, 2017, 03:38 PM   #5
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Quote:
Originally Posted by skeeter View Post
if the data set models an exponential function, then the data plot of x vs. log(y) would look linear
I don't know if my calculator can use a logarithmic scale.

Is there a way of doing different types of regression, finding a value of how well each model fits the data, and therefore a way to tell which type of regression fit the best?
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