Mean =AVERAGE()
Weighted Mean =SUMPRODUCT(weights, values) / n
Where n = SUM(weights)
Median =MEDIAN()
Mode =MODE()
Range =MAX()-MIN()
Class Width =range / number of classes All Versions of Excel Excel 2010
Variance Sample: =VAR() =VAR.S() Population: =VARP() =VAR.P()
Standard Deviation (SD) Sample: =STDEV() =STDEV.S() Population: =STDEVP() =STDEV.P() Or,=SQRT(variance) Or, =variance^0.5
Skewness =3*(AVERAGE() - MEDIAN()) / SD
Coefficient of Variation =SD / AVERAGE() * 100
Em. R 1)68 2)95 3)99.7 lower value : higher value
Lower = mean – stdev (2)(3)
Higher= mean+stdev (2)(3)
Grouped Data Weighted Mean:
=SUMPRODUCT(frequencies,class midpoints)/n
Where n = SUM(class frequencies)
Median: class that has middle frequency: =(n+1)/2
Variance:
=SUMPRODUCT(frequencies, deviations) / (n-1)
Where deviations = (midpoint - mean)^2
Population is same except divide by n.
SD: =SQRT(variance)
Chebyshev = 1 - 1 / k^2
Where k = number of standard deviations
Percentile i = percentile/100 * n
Round up if decimal; average if whole.
N= # of data values, Whole # = average it out
IQR, Outliers = Q3 - Q1 Upper Outlier =Q3 + 1.5 * IQR (75) Lower Outlier =Q1 − 1.5 * IQR (25)
Probability P(A)
P(A or B) = A / Total
= P(A) + P(B) - P(Both) P(A and B)
P(A and B)
P(A | B)
P(A | B) = P(A) * P(B)
= P(A) * P(B|A)
= P(A and B) / P(B)
= P(A|B)*P(B)
P(A|B)P(B)+P(A|Bc)P(Bc)
= P(B|A)*P(A) / P(B) Independent
Dependent
Conditional
Bayes' Rule
Permutation =PERMUT(n,r) (N=count of data values)
Combination =COMBIN(n,r) (R=size of smaller group taken from N) Discrete Distributions Expected Value: =SUMPRODUCT(x,P(x))
Variance: =SUM(x^2 * p) - (expected value^2)
SD: =SQRT(discrete variance)
Binomial Distributions

Mean: =n*p
Variance: =n*p*(1 - p)
SD: =SQRT(variance)
Probability: