1. Luka Petrović 69/2012 1/12

2. The Standard Deviation is a measure of how spread out numbers are. Its symbol is σ (the greek letter sigma) The formula is easy: it is the square root of the Variance. So now you ask, "What is the Variance?" 2/12

3. The Variance is average of the squared differences from the Mean. 3 simple steps to calculate the Variance: 1.Calculate the Mean (the simple average of the numbers) 2.Then for each number: subtract the Mean and square the result 3.Then work out the average of (2) *Reminder: we will root this value to get Standard Deviation! 3/12

4. You and your friends have just measured the heights of your dogs (in millimeters): The heights (at the shoulders) are: 600mm, 470mm, 170mm, 430mm and 300mm. 4/12

5. The mean (average) height is 394 mm. 5/12

6. Now we calculate each dog's difference from the Mean: Then square them: Maxeler part 6/12

7. And the Standard Deviation is just the square root of Variance: Standard Deviation: σ = √21,704 = 147.32... = 147 (to the nearest mm) 7/12

8. Now, we will do this using Maxeler… 8/12

9. Kernel code Final graph 9/12

10. Correct execution! Data: Random float values in range 0-100 Running on MaxCompilerVM-2015, MaxIDE (Eclipse for Maxeler) 10/12

11. Milutinovic, V., et al, Guide to DataFlow SuperComputing, Springer, 2015. Milutinovic, V., editor, Advances in Computers: DataFlow, Elsevier, 2015. Milutinovic, V. et al, Paradigm Shift in SuperComputing: DataFlow vs ControlFlow, Journal of Big Data, 2015 http://www.mathsisfun.com/ http://www.wikipedia.org/ http://www.investopedia.com/terms/s/standarddeviation.asp 11/12

12. Maxeler is fun and we hope we will get more of these: 1.Tutorials 2.Development tools 3.Community help 12/12