Linear Regression And Correlation: A Beginner's Guide by Hartshorn Scott

Author:Hartshorn, Scott [Hartshorn, Scott]
Language: eng
Format: azw3, epub
Published: 2017-06-07T16:00:00+00:00

We are showing this process for exponentials, but the same process would work for any function that had an inverse. If you can apply a function to a set of data get a linear result as the output, you can do the linear regression on that result, and then apply the inverse of that regression to find the regression of the original data.

Exponential Regression Example – Replicating Moore’s Law

Here is an example of that process in action. This data is the number of transistors on a microchip, retrieved from this Wikipedia page https://en.wikipedia.org/wiki/Transistor_count January 2017. The Excel file with that data can be downloaded here http://www.fairlynerdy.com/linear-regression-examples/.

This is the type of data that famously gave rise to Moore’s law stating that the number of transistors on a chip will double every 18 months (later revised to doubling every 2 years). No attempt was made to scrub outliers from this data. So some of these chips could be from computers or phones, be expensive or cheap.

Let’s plot the data and see what we get

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