# Can we draw a parallel between the rise (low) in **oil** and the rise (low) in inflation ?

When we look at the inflation graph and the oil graph, we can infer that there is a direct correlation.

Image: **Oil Barrel price** chart Source: Trading Economics

Image: **Inflation in the United States** by Trading Economics.

## But can we establish some mathematical correlation between the future price of a barrel of oil and inflation?

It's one thing to infer just by looking at graphs and plotting possible **trend lines** . However, **statistically** speaking, let's check if these two variables are correlated.

To begin this journey, many assumptions and adjustments have to be made. The first difficulty to be overcome is this: **inflation data** is presented every 30 days, while **future price data for a barrel of oil** is traded every minute. So, the main question is posed in *mining and pre-processing the raw data.*

To overcome this difficulty; I then decided to calculate the **average price of a barrel of oil** that occurred within a month to simplify our investigation.

The second problem in **data** **mining and preprocessing** is also challenging. Can we treat **oil prices** as a lagged variable ( **L** **ag Variable** ) ? In other words, one month's **oil prices** are only felt in the next month, and are not reflected immediately.

As we can see, the problems in generating our possible **correlation model** between the **independent variable** , in this case, **inflation** , and the **dependent variable** , here represented by **oil** , are numerous.

Image3: Table of results.

### What were the results of the first tests?

We see that the **correlation between these variables** , as organized, is less than 5%. However, our **model predicts** that 8% of the **variation in US inflation** is explained by **future oil prices** . However, our **P-Values** show us that **statistically** we have to discard the test, since it is not within the range of **95% statistical reliability** , which would prove that our **variable is indeed significant** in the variable we are trying to explain.

As a result, in our first attempt to **draw a correlation** , in the search for

*profusely.*

**creating a regression model with a single variable**failedA more technical subject today, entering into what we call **Data Science and Data Analytics.**

Follow our next posts in search of a **mathematical model** to correlate these two variables.

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