How to Do Regression Analysis in Excel with ChatGPT

Running a regression analysis in Excel used to mean digging up old statistics textbooks or watching tutorials just to build a simple forecast. Using ChatGPT, you can ditch the formulas and get straight to the insights. This article breaks down how to use ChatGPT as your copilot for conducting regression analysis in Excel, from preparing your data to interpreting the results.

What is Regression Analysis? A Quick Refresher

In simple terms, regression analysis helps you understand the relationship between different variables. Think of it like trying to predict ice cream sales based on the daily temperature. Temperature is your independent variable (the cause or input), and ice cream sales are your dependent variable (the effect or outcome). Regression analysis gives you a formula to estimate how much sales will increase for every degree the temperature rises.

You can use this for all sorts of business questions:

• How much do my sales increase for every dollar I spend on Facebook ads?

• Does the number of website visits influence the number of demo requests we receive?

• Can I predict employee retention based on their satisfaction score and salary?

The goal is always the same: to find a reliable pattern in your data that helps you predict future outcomes. You'll work with two main types:

• Simple Linear Regression: One independent variable predicting one dependent variable (e.g., Ad Spend -> Sales).

• Multiple Linear Regression: Two or more independent variables predicting an outcome (e.g., Ad Spend + Website Traffic -> Sales).

Getting Your Data Ready in Excel

Before you ask ChatGPT for help, your data needs to be clean and organized. The quality of your analysis depends entirely on the quality of your data - a concept often called "garbage in, garbage out."

For a regression analysis, structure your data in a simple table format. Each variable should have its own column, and each row should represent a single observation (like a day, a week, or a customer).

Imagine you want to see how your ad spend on different channels impacts your weekly sales. Your spreadsheet should look methodical and clear, like this:

A few tips for preparing your data:

• Use Clear Headers: Label each column distinctly (e.g., "Google Ads Spend" not just "Spend").

• Keep Data Types Consistent: Ensure number columns contain only numbers and date columns contain only dates.

• Handle Missing Data: Remove rows with blank cells or fill them with a meaningful value (like the average), but be careful as this can skew results. Simplicity is an advantage here, it's often better to just remove the row.

• Identify Your Variables: Be clear about which variable you are trying to predict (dependent variable) and which variables you are using for the prediction (independent variables). In our example, "Weekly Sales" is the dependent variable.

Using ChatGPT to Do the Heavy Lifting

Once your data is tidy, you can start using ChatGPT as your personal Excel wizard. You don't need to know the specific formulas or steps, just describe your data and what you want to achieve. ChatGPT can guide you through using Excel’s built-in formulas or the more powerful Data Analysis ToolPak.

Option 1: Ask for Specific Formulas

For simple linear regression, you can use Excel's SLOPE and INTERCEPT functions. Instead of memorizing how they work, you can just ask ChatGPT to generate the formula for you.

Step 1: Write a Clear Prompt

Describe your data and what you're trying to find. The more specific your prompt, the better the answer will be.

Example Prompt for a Simple Regression:

"I have an Excel sheet where 'Facebook Ads Spend' is in column B (from B2 to B51) and 'Weekly Sales' is in column C (from C2 to C51). I want to perform a simple linear regression. What are the Excel formulas to find the slope and the intercept?"

Step 2: Get and Apply the Formulas

ChatGPT will likely give you something like this:

"Of course! Here are the formulas you need:

To find the slope (the amount sales increase for each dollar of ad spend):=SLOPE(C2:C51, B2:B51)

To find the intercept (your baseline sales with zero ad spend):=INTERCEPT(C2:C51, B2:B51)

Make sure your known_y's (your dependent variable, Sales) comes first inside the formula."

Now, just copy these formulas into empty cells in your Excel worksheet. For example, if the slope is 15.5 and the intercept is 2,500, your regression formula is: Sales = 2,500 + (15.5 * Ad Spend). You can now use this to forecast future sales.

While this is quick for simple analysis, it doesn't give you crucial information like the R-squared value, which tells you how accurate your model is. For that, the Data Analysis ToolPak is a much better choice.

Option 2: Use the Data Analysis ToolPak (with ChatGPT as a Guide)

The Data Analysis ToolPak is a free Excel add-in that performs complex statistical analyses, including multiple regression. It's the most powerful native tool in Excel for this task. Don't worry if you’ve never used it - ChatGPT can walk you through every click.

Step 1: Make Sure the ToolPak is Enabled

The ToolPak isn't enabled by default. You can ask ChatGPT how to turn it on, and it will give you these steps:

1. Go to File > Options.

2. Click on Add-Ins in the left pane.

3. At the bottom, where it says "Manage:", select Excel Add-ins and click Go.

4. Check the box next to "Analysis ToolPak" and click OK.

You'll now have a "Data Analysis" button under the "Data" tab in your Excel ribbon.

Step 2: Prompt ChatGPT for Step-by-Step Instructions

Now, ask ChatGPT to guide you through the process for your specific dataset.

Example Prompt for Multiple Regression:

"How do I run a multiple regression analysis in Excel using the Data Analysis ToolPak? My data is set up with 'Weekly Sales' in column D, 'Google Ads Spend' in column B, and 'Facebook Ads Spend' in column C. All my data, including headers, is from row 1 to row 53."

Step 3: Follow ChatGPT’s Instructions in Excel

ChatGPT will provide a clear, step-by-step checklist:

1. Click on the Data tab and select Data Analysis.

2. From the list, choose Regression and click OK.

3. In the dialog box, you'll need to fill in a few fields:

• Input Y Range: This is your dependent variable (what you're predicting). Select your 'Weekly Sales' data (D1:D53).

• Input X Range: These are your independent variables. Select your 'Google Ads Spend' and 'Facebook Ads Spend' data at the same time (B1:C53).

• Check the Labels box since you included headers in your selection. This tells Excel to use the first row as names for the variables in the output table.

• Choose an Output Range. This is where you want the results to appear. You can pick an empty cell in your current sheet or have it show up in a new worksheet.

1. Click OK. Excel will now perform the regression analysis and generate a detailed summary report.

Asking ChatGPT to Interpret Your Results

Excel will produce a table full of statistics like R-squared, coefficients, and P-values. This output can be overwhelming if you're not a statistician. A huge advantage of using ChatGPT is its ability to translate this technical information into plain English.

You can simply copy the key parts of the summary output and ask ChatGPT to explain them.

Example Prompt for Interpretation:

"I ran a regression analysis in Excel and got this output. Can you explain what it means in simple terms for my business?"

Here's the data:

R Square: 0.85

Coefficients:Intercept: 1,500Google Ads Spend: 10.2Facebook Ads Spend: 7.8

P-values:Google Ads Spend: 0.001Facebook Ads Spend: 0.04

ChatGPT’s Interpreted Response:

ChatGPT would provide a clear summary like this:

• Overall Model Accuracy (R-Squared): "Your model is a great fit! An R-squared of 0.85 means that 85% of the change in your weekly sales can be explained by your combined spending on Google and Facebook ads. This is a very strong relationship."

• The Prediction Formula (Coefficients): "Your formula for predicting sales is: Sales = 1,500 + (10.2 * Google Ads Spend) + (7.8 * Facebook Ads Spend). This is your predictive engine."

• Impact of Each Channel: "For every $1 you spend on Google Ads, you can expect sales to increase by about $10.20, assuming your Facebook spend stays the same. Similarly, every $1 spent on Facebook Ads brings about a $7.80 increase in sales."

• Statistical Significance (P-values): "Both ad channels are statistically significant predictors of sales because their P-values (0.001 and 0.04) are less than the common threshold of 0.05. This means the relationships you've found are not likely due to random chance."

With this simple translation, you've gone from a table of confusing numbers to a clear, actionable strategy: Google Ads appear to be delivering a higher return in this model, so you might consider allocating more budget there.

Final Thoughts

By pairing the computational power of Excel with the conversational intelligence of ChatGPT, you can perform sophisticated data analysis without needing a degree in statistics. This combination allows you to test hypotheses, build forecasts, and uncover the real drivers of your business performance, all within a familiar spreadsheet environment.

We know that even with AI assistance, pulling reports from multiple sources and wrestling with spreadsheets can be a time-consuming chore. We built Graphed to solve this a different way. Instead of piecing data together manually, you just connect your sales and marketing platforms, then ask questions in plain English like, "show me the ROI of my ad campaigns last month." We instantly build live, interactive dashboards that answer your questions, so you spend less time gathering data and more time acting on it.