Excel Moving Average with Analysis TookPak Add in

In Excel, you can create a moving average, also called a rolling average or running average or simple moving average (SMA). A moving average creates a series of data points by creating a series of averages of different subsets of the data set. A moving average smooths out short-term fluctuations and highlights longer-term trends or cycles. In Excel, you can use the Analysis ToolPak feature to calculate the moving average. You have to install the Analysis ToolPak, which I cover in the video.

You don't have to use the Analysis TookPak for a moving average, but there are many other features that come with the Analysis TookPak. A list of the features is below.

Chapters:
0:00 Intro
0:20 Moving Average explained
1:25 Install Analysis ToolPak
2:30 Using Moving Average
5:00 Closing comments

Install the Analysis ToolPak in Excel
1) Click File, then Options
2) Select Add-ins
3) Click GO and check Analysis ToolPak and select OK.
The Analysis ToolPak will show on the Data tab in Excel.
Screenshot of the Data Analysis dialog box with Moving Average feature

Other items included in the Analysis ToolPak in Excel
Anova: Single Factor
Anova: Two-Factor With Replication
Anova: Two-Factor Without Replication
Correlation
Covariance
Descriptive Statistics
Exponential Smoothing
F-Test Two-Sample for Variances
Fourier Analysis
Histogram
Moving Average
Random Number Generation
Rank and Percentile Regression Sampling

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[richardhay]

I have used analysis tool pak for years. It is undertaught and underused. Great video.

[RHKhan-vmvu]

That's very helpful. Thanks for sharing! 🙂

[letiiayala]

Great video, I found it very helpful, thanks for your contribution :D

[PushpaChitrakar]

Analysis ToolPak Add in and Trendline shifted the curve forward.

[pcmobitab]

Hey Chris thanks a lot! I have one question whats the difference between rolling average and moving average. Using pandas package in python when I applied rolling mean it exactly worked like this. So this is SMA or simple moving average. But then using the package statsmodels, the ARIMA model if we try to calculate the MA(q) by applying (p, d, q) =(0, 0, 10) then it gives different results. is ARIMA moving average that basically is forecasting based on past error values is different? I am bit confused with the same terminologies here.. Basically I want to understand the math behind ARIMA's moving average and how it differs from this.

[gadijamohamed]

Hi chris anyway i can ask u for help with an assignment