# Linear and non linear relationship in MET office data - A-level maths

I am looking for relationships between different variables in a set of MET office data. The data set is for the months May to October in 2015 and 1987 in various places in the UK. The variables measured are listed at the bottom of this post.

To add some context, the data set is part of the A-level maths specification (spreadsheet linked here).

I am interested in how this data set would be analysed in a meteorological setting and replicate it in a maths lesson

An example would be to calculate the PMCC and perform a hypothesis test to see if it is statistically significant.

For example, one linear relationship would be between sunshine and cloud cover I lack the knowledge to know which variables would be connected and their relationships. It would be ideal to discover linear relationships of the form:

$$y= a +bx$$ $$\log(y)=a+ b\log(x)$$ $$\log(y)=a+ bx$$

Variables measured in the large dataset:

Daily Mean Temperature

Daily Total Rainfall

Daily Total Sunshine

Daily Maximum Relative Humidity

Daily Mean Windspeed

Daily Maximum Gust

Daily Mean Wind Direction

Daily Maximum Gust Direction

Cloud Cover

Visibility

Pressure

• Think there was a very similar question asked around here many years ago on what variables are connected to each other, I just can't find it Jun 30 at 12:05
• Thanks @JeopardyTempest I will keep looking. I have also asked the question on the Math educators stack exchange in the hope of getting an answer matheducators.stackexchange.com/q/26587/3407 Jul 1 at 17:08