Standard deviation

Assuming this is a sample of the population (CTRL+Shift+Enter): =STDEV.S(IF($A$2:$A$7="A",$B$2:$B$7,FALSE)) More on reddit.com

The best way to detect outliers is either the Grubbs Test (which assumes normality in the data excluding the outlier) or Tukey's BoxPlot test which is robust to normality. Grubb's test is powerful but is a bit messy so I would suggest using Tukey's Boxplot test: Inter Quartile Range (IQR) = 75th percentile - 25th percentile. A potential outlier occurs if it exceeds 75th percentile + 1.5 IQR or below 25th - 1.5 IQR. An extreme outlier occurs if it exceeds 75th percentile + 3 IQR or below 25th - 3 IQR. I'll leave you to figure out the Excel formulas (or vba). There are commercial addins that do both methods as well.. Edit: this isn't solving your specific request to compute the stdev but I wanted to give you better methods of detection than 3 or 4 stdevs. More on reddit.com

Standard deviation will be square root of (1 - p)p where p = 0.56 Standard error is of an estimate so you can calculate that for your estimate of proportion being 0.56. Basically it’s the std deviation decided by sqrt of sample size . The larger the sample the more you can trust that the proportion is 0.56 More on reddit.com

You're looking for the pooled variance: https://en.wikipedia.org/wiki/Pooled_variance Pooled variance is a weighted average of each variance, weighted by the degrees of freedom (n-1) of each set. Once you have the pooled variance, you can take the square root to get the pooled standard deviation. Say you have two data sets: n_1 = 10; mean_1 = 15; sd_1 = 3 n_2 = 15; mean_2 = 12; sd_2 = 2 Then the pooled variance would be: sd_p2 = ( (10-1)*32 + (15-1)*22 ) / (10+15-2) sd_p2 = 5.956521739 And then take the square root to get the pooled standard deviation: sd_p = 2.440598644 Notice that the pooled standard deviation is closer to the second set, because the second set is bigger. Also notice that the mean doesn't factor into the calculation. More on reddit.com