Statistics Formulas

Statistics Formulas

Statistics is a branch of mathematics which deals with numbers and data analysis. Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. Statistical theory defines a statistic as a function of a sample where the function itself is independent of the sample’s distribution.

In short, Statistics is associated with collecting, classifying, arranging and presenting numerical data. It allows us to interpret various results from it and forecast many possibilities. Statistics deals with facts, observations and information which are in the form of numeric data only. With the help of statistics, we are able to find various measures of central tendencies and the deviation of different values from the center.

Statistics Formula Sheet

The important statistics formulas are listed in the chart below:

Mean
\(\begin{array}{l}\bar{x}=\frac{\sum x}{n}\end{array} \)
x = Observations given
n = Total number of observations
Median If n is odd, then
M =
\(\begin{array}{l}(\frac{n+1}{2})\end{array} \)
\(\begin{array}{l}^{th}\end{array} \)
term
If n is even, then
M =
\(\begin{array}{l}\frac{(\frac{n}{2})^{th}term+(\frac{n}{2}+1)^{th}term}{2}\end{array} \)
n = Total number of observations
Mode The value which occurs most frequently
Variance
\(\begin{array}{l}\sigma ^{2}\end{array} \)
=
\(\begin{array}{l}\frac{\sum (x-\bar{x})^{2}}{n}\end{array} \)
x = Observations given
\(\begin{array}{l}\bar{x}\end{array} \)
= Mean
n = Total number of observations
Standard Deviation
\(\begin{array}{l}S = \sigma = \sqrt{\frac{\sum (x-\bar{x})^{2}}{n}}\end{array} \)
x = Observations given
\(\begin{array}{l}\bar{x}\end{array} \)
= Mean
n = Total number of observations

Additional guidelines on all statistics formula are given below. See the below list where all statistical formulas are listed.

More topics in Statistics Formulas
Population Mean Formula Mean Median Mode Formula
Mean Deviation Formula Standard Deviation Formula
Quartile Formula Correlation Coefficient Formula
Variance Formula Coefficient of Determination Formula
Margin of Error Formula Relative Frequency Formula
Linear Regression Formula T Test Formula
F Test Formula Gaussian Distribution Formula
Chi Square Formula Confidence Interval Formula
Sample Size Formula Z score Formula
Anova Formula Degrees of Freedom Formula
Central Limit Theorem Formula Standard Error Formula
Cpk Formula R Squared Formula
Sampling Error Formula Root Mean Square Formula
Line of Best Fit Formula Cp Formula
Signal to Noise Ratio Formula Frequency Distribution Formula
Hypothesis Testing Formula Statistical Significance Formula

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