# PEARSON: Excel Formulas Explained

Let's face it, Excel can be a bit intimidating. With so many buttons, tabs, and functions, where do you even start?

Well, fear not my friends, because today we're going to break down one of the most important aspects of using Excel: formulas. Specifically, we're going to take a closer look at some of the most useful formulas offered by one of Excel's biggest players: PEARSON.

## What is PEARSON?

For those unfamiliar with PEARSON, it's a statistical function in Excel that calculates the correlation coefficient between two data sets. But, what does that even mean?

Think of it this way. Let's say you had two columns in Excel, one with the average temperature of a city and another with the number of ice cream cones sold that day. If you wanted to see if there was a relationship between the two, you would use the PEARSON formula to get a correlation coefficient. The coefficient will give you an idea of how closely related the two data sets are.

But enough with the stuffy definitions, let's get into the good stuff. Here are a few PEARSON formulas that can help take your Excel skills to the next level:

## PEARSON Function Formula

The first formula we're going to look at is pretty straightforward. It's the basic PEARSON function formula. Here's what it looks like:

``=PEARSON(array1,array2)``

Where `array1` and `array2` are the two data sets you want to compare. Simply input the arrays and hit enter to get your correlation coefficient. It's that easy!

## PEARSON Nested Function Formula

If you're feeling fancy and want to add a bit more specificity to your formula, you can use the PEARSON nested function formula. Here's what it looks like:

``=IFERROR(ABS(PEARSON(array1,array2)),0)``

What does this extra code do? Well, the `IFERROR` function helps to catch errors that can occur for various reasons. The `ABS` function then takes the absolute value of the correlation coefficient to ensure it's always positive. Lastly, the `0` at the end of the formula specifies what the value should be if there's an error.

It may be a bit more complicated, but once you get the hang of it, you'll feel like an Excel pro.

## PEARSON Correlation Heatmap Formula

This next formula is extra cool because it creates a heatmap to visualize the correlation between your data sets. Here's the formula:

``=CHOOSE(1+INT(ABS(PEARSON(array1,array2))*10), "No correlation", "Very weak correlation", "Weak correlation", "Moderate correlation","Strong correlation", "Very strong correlation")``

This is a bit more complicated than the previous formulas but it's worth it. The heatmap you get from this formula will show a range of colors from cool to warm, where cool being no correlation and warm being a strong correlation. With this formula, you can see the correlation between your data sets more vividly than just reading a number.

## Wrapping up

These three PEARSON formulas are just the tip of the iceberg when it comes to using Excel for statistical analysis. But mastering these can help you get started on the path to becoming an Excel guru.

So, the next time you open up an Excel spreadsheet, don't be intimidated. Just remember - PEARSON has your back.

Now, if you'll excuse me, I have to go heat up my coffee for round two of Excel madness.