It is a measure of the spread of the outcomes around the mean value.
In general you cannot. You will need to know more about the distribution of the variable - you cannot assume that the distribution is uniform or Normal.
Yes. Consider 1,1,1,1,1,3,5,5,5,5,5 and 0,3,3,3,3,3,3,3,3,3,5 Set 1: Range = 4, sd = 2.00 Set 2: Range = 5, sd = 1.14
Neither.
Here's how you do it in Excel: use the function =STDEV(<range with data>). That function calculates standard deviation for a sample.
no
It is a measure of the spread of the outcomes around the mean value.
in a normal distribution, the mean plus or minus one standard deviation covers 68.2% of the data. If you use two standard deviations, then you will cover approx. 95.5%, and three will earn you 99.7% coverage
In general you cannot. You will need to know more about the distribution of the variable - you cannot assume that the distribution is uniform or Normal.
Some measures:Range,Interquartile range,Interpercentile ranges,Mean absolute deviation,Variance,Standard deviation.Some measures:Range,Interquartile range,Interpercentile ranges,Mean absolute deviation,Variance,Standard deviation.Some measures:Range,Interquartile range,Interpercentile ranges,Mean absolute deviation,Variance,Standard deviation.Some measures:Range,Interquartile range,Interpercentile ranges,Mean absolute deviation,Variance,Standard deviation.
I think its better to use range deviation in any distribution because it doesn't cause any trouble
The range is 12 and the standard deviation is 3.822448314.
On the standard deviation. It has no effect on the IQR.
Type your answer here... It depends what percentage of the total data you want to embrace. 99.73% of the total distribution lies between minus to plus 3 standard deviations. That's usually the benchmark range.
In general, you cannot. If the distribution can be assumed to be Gaussian [Normal] then you could use z-scores.
Yes. Consider 1,1,1,1,1,3,5,5,5,5,5 and 0,3,3,3,3,3,3,3,3,3,5 Set 1: Range = 4, sd = 2.00 Set 2: Range = 5, sd = 1.14
The range is 9 and 3.01 is the standard deviation.