Monthly Sales Forecast with Seasonality and Trend - EXCEL regression with dummy variables

Welcome to our comprehensive tutorial on Monthly Sales Forecasting using Excel Regression with Dummy Variables, where we'll guide you through the intricacies of forecasting sales with both seasonality and trend. Whether you're a business analyst, data enthusiast, or just looking to enhance your Excel skills, this video is your gateway to mastering the art of accurate sales predictions.

📊 In this step-by-step tutorial, you'll learn:
1️⃣ The fundamentals of regression analysis in Excel, leveraging the powerful Data Analysis Tool Pack.
2️⃣ How to effectively capture and incorporate seasonality into your sales forecasts using dummy variables.
3️⃣ The importance of recognizing and accounting for trends in your data to make more accurate predictions.
4️⃣ A deep dive into Winter's Smoothing Method, demystifying this widely-used forecasting technique.
5️⃣ Practical tips and best practices to ensure your forecasts are reliable and actionable.

Sales forecasting is a critical aspect of business planning, helping you make informed decisions on inventory management, resource allocation, and overall business strategy. Whether you're dealing with historical sales data, financial planning, or simply want to gain a deeper understanding of predictive analytics, this tutorial will provide you with the knowledge and skills you need.

===== CHAPTERS =====
2:01 - Create the Dummy Variables

3:31 - The Regression tool in Excel's Analysis Tool pack

7:01 - Create the Regression Model

10:00 - Visualize with Excel Chart

#ExcelRegression #SalesForecasting #DataAnalysis #DummyVariables #WinterSmoothing #BusinessAnalytics #ExcelTutorial #DataScience #TrendAnalysis #SeasonalityForecasting #BusinessIntelligence

[JohnKamauNjenga]

Simple and elegantly presented. Was working on a forecast and other descriptions online were abhorrent to say least. The error range was HUGE, but thanks to you my standard error reduced to 2%. Asante Sana!!!🤗

[chilarmah]

Great work! Solved a problem I have been working on for days.

[johnshepherd]

thank you very much, this really helped me a lot!

[EricD_]

Great content explained in detail! Amazing!

[adityavedam]

Could you share the data file for Practice please ?

[marcelporcescu]

But how can we do daily. I tried but it show only 16 variable maximum, but we have 30 days

[sisayzewde]

I think residual should be zero or close to zero! right? but in your case it is too much; so, can we say your forecast is good?

[ahuhokay]

u are the best bro thank you for the help🙏

[roshandhumal]

Sir, could you please explain us why we have to lock 🔒 intercept, please explain and please explain me about p value.

[merjenorazmammedova]

Thank you for the video, it is really helpful!

[cbscseg]

If I have to do the same thing but on a day level
How can I achieved that?

[emilytran]

Thank you for your great video! Do you think this work correctly with 12 months data historical and some month value = 0 as well ? I look forward to hearing your advices.
Then how can we apply for multi sku products.

[davidjosevarelagarcia]

Great video, is very usefull, thanks. i have a question, why dont use december when you transpose the months?

[sisayzewde]

and also, why you used three years data? what will be wrong if I use two- or four-years data?

[Seftehandle]

P value error #num and some very low coefficients for significance f 0.8465 f 0.56 p greater than 0.05. please do similar videos on different. Stat methods

[aapriyanka]

Excellent sir. Can we use the same process for 5 year forecast. Please do reply sir

[sacca]

Hello Sir
Where can I get the Excel worksheet to follow your presentation. Thanks

[roshandhumal]

Sir what If we have Jan to March instead of Jan to Dev
Because of I have value from Jan to March and when I am doing the method the out is not showing right could you please give me a hint

[kiamarieamedao]

Hello! Don't know what I did wrong but when I tried to use the Regression tool in Excel's pack, it said "The number of rows and columns in X range cannot be the same."

[nikomou]

so "t" is for trend and "jan" thru "nov" is for seasonality. am i correct