# Multiple Linear Regression with small dataset

I have a dataset of 30 social variables such as Facebook Likes, Posts, Comments, etc. I would like to see if these variables predict Website Views.

MY problem is I only have 3 months of data- or 3 data points. Thus I have a 3 by 30 dataset. My question is, how do I model with such few data points but lots of variables?

In addition, I would love a resource that walks through regression in R. My data does not even remotely look linear, so I don't know what to do next. Suggestions?

– sheß
Commented Apr 21, 2016 at 22:24
• 3 observations, 30 variables implies that you need many more observations. Even 30 observations and 3 variables would be a stretch. Commented Apr 21, 2016 at 22:37
• This can not be done. Your linear regression is what we call underdetermined. Because you have way more variables than you do observations, linear regression won't be able to pick out coefficients that minimize the sum of squared errors. There are, literally, an infinite number of coefficients that would do so, which doesn't sound very useful. You are going to need to wait for more data. Commented Jul 7, 2019 at 15:51
• You need more data. People are suggesting using regularization or local methods, but both will give highly variable results. Frankly, your inference will be questionable even if you take a simple average.
– Josh
Commented Jul 7, 2019 at 16:22
• I may be missing something, but why do 3 months of visits result in 3 data points? Why not summarize by day? That would give you 30x more observations. Commented Jul 8, 2019 at 19:28