- #1

Master1022

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- TL;DR Summary
- I am conducting a linear regression using climate time series data (temperature, precipitation, etc.) in order to predict how a certain device will perform. Should I remove seasonality from the data even if we expect the device to perform differently at different times of the year?

Hi,

I am not sure what the correct forum is for this question.

I am planning to conduct a

[tex] \begin{equation}

\text{device output} = f(\text{temperature}, \text{precipitation}, \text{etc.})

\end{equation}

[/tex]

and given the nature of the device, I expect that it will have less output in the summer and more in the winter. I am working with one year's worth of data to train the model and have some predicted data from the future. Therefore, I think the different temperature levels are very important factors in the regression. However, I have been told that I ought to 'remove seasonality from the data' (no further clarification was given upon asking again).

I have done some reading on the internet, but have been unable to find any information. Any help would be greatly appreciated.

I am not sure what the correct forum is for this question.

**Question:**When do we need to remove seasonality from time series data to do a regression analysis?**Context:**I am planning to conduct a

**prediction analysis**where I want to find out how a device performs. I hope to estimate a function that takes the form:[tex] \begin{equation}

\text{device output} = f(\text{temperature}, \text{precipitation}, \text{etc.})

\end{equation}

[/tex]

and given the nature of the device, I expect that it will have less output in the summer and more in the winter. I am working with one year's worth of data to train the model and have some predicted data from the future. Therefore, I think the different temperature levels are very important factors in the regression. However, I have been told that I ought to 'remove seasonality from the data' (no further clarification was given upon asking again).

I have done some reading on the internet, but have been unable to find any information. Any help would be greatly appreciated.