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Statistics Calculator

Compute Mean, Median, Mode and Min, Max, Quartiles (Q1, Q2, Q3) along with Variance, Standard Deviation, Standard Error. Plot 3 sigma with histogram.

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Stats Calculator


Compute mean, median, std deviation - Enter your data as comma separated values or with spaces. You can also import csv or any data file with delimiters
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Stat Results

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Metric Result
Count 12
Sum 2218.15
Min 50.78
Max 469.82
Range 419.04
Mean 184.846
Median 151.05
Mode
378.32,
257.63,
469.82,
184.9,
50.78,
240.71,
57.35,
87.8,
117.2,
105.11,
53.82,
214.71
Quartile 64.963 151.05 253.4
Outlier none
Variance16641.75
Standard Deviation 129.003
Standard Error 37.24
Sample Variance 18154.636
Sample Standard Deviation 134.739
Sample Standard Error 38.896

Population Statistics vs Sampling Statistics

  • In Population Statistics, the dataset represents the full data and the exact variance, standard deviation is calculated

  • Example is Scores of Students in a class, temperature recorded in a month

Population Statistics

Metric Formula Description
Variance S2 = 1 n - 1 ∑ i = 1 n ( x i - x ¯ ) 2 where, n is Number of observations in sample, xi is ith observation in the sample and x ¯ is Sample mean
Standard Deviation S = 1 n - 1 ∑ i = Square root(1 n ( x i - x ¯ ) 2) where, n is Number of observations in sample, xi is ith observation in the sample and x ¯ is Sample mean
Standard Error SE = SD/Square root(n) where, SE is Standard Error, SD is standard deviation and n is total numbers
  • In Sample Statistics, it represents a sampling of the data and that is used to project for an entire category

  • Example is Average Height of Male and Females in different countries

Sample Statistics

Metric Formula Description
Sample Variance S2 = (1/ n - 1 ) * ∑ i( x i - x ¯ ) where, n is Number of observations in sample, xi is individual values in sample and x ¯ is Sample mean
Sample Standard Deviation S = Square root((1/ n - 1 ) * ∑ i( x i - x ¯ ) 2) where, n is Number of observations in sample, xi is individual values in sample and x ¯ is Sample mean
Sample Standard Error SSE = SSD/Square root(n) where, SSE is Sample Standard Error, SSD is sample standard deviation and n is total numbers

Histogram Chart

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Class Range Frequency
1 0 - 43 0
2 44 - 87 3
3 88 - 131 2
4 132 - 175 0
5 176 - 219 2
6 220 - 263 2
7 264 - 307 0
8 308 - 351 0
9 352 - 395 1
10 396 - 439 0
11 440 - 483 1
12 484 - 527 0
Sigma Empirical formula Range Frequency %
1 sigma mean - 1 * SD mean + 1 * SD 55.8430 - 313.8490 8 66.7%
2 sigma mean - 2 * SD mean + 2 * SD -73.1600 - 442.8520 11 91.7%
3 sigma mean - 3 * SD mean + 3 * SD -202.1630 - 571.8550 12 100.0%
  • 68-95-99.7 rule states that in a typical normal distribution, 68% of the data points fall within +/- 1 standard deviation of the mean.

  • 95% within 2 standard deviation from the mean Almost 100% within 3 standard deviations from the mean


Statistical Formulae

Formula to calculate Count

Count = n

where n is the total number of items in the dataset


Formula to calculate Sum

Sum = a1+a2+...+an

where, n is a1, a2, an, are data values


Formula to calculate Minimum

Min = 1/2 (r+s-|r-s|)

where, r is first number and s is second number


Formula to calculate Maximum

Max = 1/2 (r+s+|r-s|)

where, r is first number and s is second number


Formula to calculate Range

Range = max-min

where, max is maximum number and min is minimum number


Formula to calculate Mean

Mean = 1/n(a1+a2+...+an)

where, n is the number of observation and a1,a2,an are data values


Formula to calculate Median

Median = [(n + 1) / 2]th term

where, n is the number of observation


Formula to calculate Mode

Mode = L + (fm-f1)h /(fm-f1)+(fm-f2)

where, l is Lower limit Mode of modal class,fm is Frequency of modal class,f1 is Frequency of class preceding the modal class, f2 is Frequency of class succeeding the modal class,h is Size of class interval


Formula to calculate Quartile

Q1 = ((n+1)/4)

Q2 = ((n+1)/2)

Q3 = (3(n+1)/4)

where, q1 is first quartile, q2 is second quartile, q3 is third quartile and n is integer numbers


Formula to calculate Outlier

U = q3 + 1.5 (q3-q1)

L = q1 - 1.5 (q3-q1)

where, U is Upper Limit and L is Lower Limit and q1 is first quartile and q3 is third quartile


Formula to calculate Variance

S2 = 1 n - 1 ∑ i = 1 n ( x i - x ¯ ) 2

where, n is Number of observations in dataset, xi is ith observation in the sample and x ¯ is mean


Formula to calculate Standard Deviation

SD = 1 n - 1 ∑ i = Square root(1 n ( x i - x ¯ ) 2)

where, n is Number of observations in sample, xi is ith observation in the sample and x ¯ is Sample mean


Formula to calculate Standard Error

SE = SD/Square root(n)

where, SE is Standard Error, SD is standard deviation and n is total numbers


Formula to calculate Sample Variance

S2 = (1/ n - 1 ) * ∑ i( x i - x ¯ )

where, n is Number of observations in sample, xi is individual values in sample and x ¯ is Sample mean


Formula to calculate Sample Standard Deviation

S = Square root((1/ n - 1 ) * ∑ i( x i - x ¯ ) 2)

where, n is Number of observations in sample, xi is individual values in sample and x ¯ is Sample mean


Formula to calculate Sample Standard Error

SSE = SSD/Square root(n)

where, SSE is Sample Standard Error, SSD is sample standard deviation and n is total numbers


Formula to calculate Sigma

1 Sigma = Mean - 1 * Standard Deviation , Mean + 1 * Standard Deviation

2 Sigma = Mean - 2 * Standard Deviation , Mean + 2 * Standard Deviation

3 Sigma = Mean - 3 * Standard Deviation , Mean + 3 * Standard Deviation


Formula to calculate Class Interval Width

CIW = SD / 3

where, SD is standard deviation