Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set

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[@pearlylissanu]

16:34 Formula for Standard Deviation (SD) using mean 23:28 Second formula for SD (without finding mean) 54:34 SD sample vs. population 1:04:01 Calculator

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58:10 Variance 1:50:44 Coefficient of Varience (CV) 1:54:27 Formula for CV

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31:24 I like how squaring x-*x* (bolded x actually has a bar above it) gives you (x-x^2)^2. That makes total sense.

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[@hailongvt2]

16:34 Formula for Standard Deviation (SD) using mean 23:28 Second formula for SD (without finding mean) 54:34 SD sample vs. population 1:04:01 Calculator 58:10 Variance 1:50:44 Coefficient of Varience (CV) 1:54:27 Formula for CV Thanks @pearlylissanu for the original time stamp

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[@iamasian329]

For anyone interested, at 56:12 he says there isn't a corollary equation for the population standard deviation equation he wrote on the board, but there is. You basically derive it the same way he derived the alternate sample standard deviation. Sal's video helps explain that kzbin.info/www/bejne/qYO5eJaPfM-IoZo

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[@bhumikalamba186]

the dataset that is within 2 standard deviations of the mean is likely and is usual, whereas the ones falling outside of these standard deviations is unusual data.

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THANK YOU so much I finally understand standard deviation!!!

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[@drudru5992]

If we do the actual reality math it’s a different value. The actual differences between x and the mean are5,3,8 which total 16. Then divide by 3 to get the average of the distances. As you see doesn’t come out to 7. Reality doesn’t equate to formula.

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[@mycotina6438]

Great video prof, but I think the explanation for why we use the squared the difference between the data value and the mean in calculating the standard deviation is a bit off. Negative data point and a positive mean doesn't cancel each other out. For example, consider a data point of -6 and a mean of 6, then (x - x_bar) would be (-6 - 6) which is -12. So it doesn't justify why we can't use absolute value instead of squaring it to get a "positive" distance. Actually, the calculation using an absolute value even has its own name, called the "mean deviation". It is just that the squared version has nicer mathematical properties and therefore more commonly used. There's an interesting discussion on the mathematic stackexchange for this, just try to google it!

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Hello, What an amazing explanation correlating to some practical examples. I am looking for some more insight on the relation between the Standard deviation and the data values. Regards

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Why do we need to have variance and standard deviation? What I mean to say is, what are some practical instances where using the variance is better than using the standard deviation (or the other way around)?

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[@aymanm.alotaibi7652]

I have question If allowed me: on 20:32 why we didn’t us the absolute value to standard deviations instead of squaring?

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