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Simple Stats

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Last modified by
on
Mar 4, 2025, 5:36:43 PM
Created by
on
Jan 31, 2017, 6:50:12 PM
Observational Stats=f(x,y,z,...
(x)"Numeric Observations"

The Simple Statistics calculator computes the most common observational statistics for a set of comma separated numbers.. 

INSTRUCTIONS: Enter the following:

  • (x) Numeric Observations.  Enter comma separated numeric values e.g. (4,-1.2,8,9).

STATISTICS: The calculator returns the descriptive statistics below for the identified column.  

  • count - number (n) of values in the column.
  • min - minimum value
  • max - maximum value
  • sum(Σx)  - sum of the values in a set.
  • Σx² - sum of the squared values
  • (Σx)² - square of the summed values.
  • mean - mean (average) of values
  • median - middle ordered value
  • mid point - mid point of value range
  • mode - most frequent observation
  • range - difference between the max and the min.
  • MAD -  Mean Absolute Deviation
  • SDOM - Standard Deviation of Mean
  • sort up - values in ascending order.
  • sort down - values in descending order.
  • var-pop - population variance of the values
  • sd-pop - population standard deviation of the values
  • var-sample - sample variance of the values
  • sd-sample - sample standard deviation of the values

How to Enter Data

Enter the data in comma separated values

The Math

The formulas for the statistics are as follows:

sum

     S = sum(x)

sum of squares

      Σx²= sum(x^2)

square of the sum

     (Σx)² = (sum(x))^2

averages

  • mean:     mu = (sum(x))/n  where n is the number of observations
  • median:  middle value if in an odd number of observations.  If there is an even number of observations, it's the average of the two middle values.
  • mid-point:  mp = (min + max)/2

variance

  • Population Variance: sigma^2 = (sum_1^n(x_n-mu)^2)/n
  • Sample Variance: sigma^2 = (sum_1^n(x_n-mu)^2)/(n-1)

standard deviation

  • Population Standard Deviation:   sigma = sqrt((sum_1^n(x_n-mu)^2)/n)
  • Sample Standard Deviation:   sigma = sqrt((sum_1^n(x_n-mu)^2)/(n-1))

Mean Absolute Deviation

  • MAD = 1/n sum_(i=1)^n | x_i - barx |

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