By Kardi Teknomo, PhD .

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There is a better way to compute average of a sequence of large measurement data. You donít need to store all the measurement data. All you need is to compute the current average Time Average is the current measurement data Time Average and the previous average Time Average . The formula is as follow

Time Average (3)

Click here to see my proof of above formula

Since the subscript Time Average start at 1, then Time Average is undefined. For convenient, we can put zero (or any number) to give the correct answer.

Using the previous measurement data of 4, 6, 12, 9 we can get exactly the same result of average as the usual computation method, but in more efficient way. Table below show the computation using the recursive average.

Time

( Time Average )

Measurement

( Time Average )

Average

( Time Average )

1

Time Average

Time Average

2

Time Average

Time Average

3

Time Average

Time Average

4

Time Average

Time Average


The interactive program below you may type your input (only number is accepted) one at a time, then press "Input" button. To compute the time average based on your current available data. Click "Reset" button to restart. Alternatively, click "Random Input" button repeatedly to create simulated data. You need to input at least two data points to make the chart.

Current input data

Current Average:
0

Previous Average:
0

Number of data:
0


List of your inputted data:
None

None

If you click Random input for about more than say 25 points, you will notice that the time average is not constant. The time average keeps changing over time. Compare this result with the constant average of traditional mean and average .

In the next section, you will learn the characteristic of time average.

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These tutorial is copyrighted .

Preferable reference for this tutorial is

Teknomo, Kardi. (2006) Recursive Average and Variance.
http://people.revoledu.com/kardi/tutorial/RecursiveStatistic/index.html