Day 1 - Team B (2)

Chi - Square Test

Its often the shorthand of  "Pearson's chi-squared test"

There are two statistical procedures to test hypotheses 

- Parametric Statistical Procedures ( ex. T test , F test )

- Non-parametric Statistical Procedures ( ex. Chi-Square test )

Parametric statistical procedures test hypotheses based on the assumption that 

• The samples come from populations that are normally distributed.
• There is homogeneity of variance (variances within groups are the same).
• The level of measurement for parametric tests is assumed to be interval or at least ordinal.

Non-parametric statistical procedures test hypotheses that do not require normal distribution or variance assumptions about the populations from which the samples were drawn and are designed for ordinal or nominal data.

Chi-squared test is used to assess two types of comparison: 

• Tests of goodness of fit

A test of goodness of fit establishes whether or not an observed frequency distribution differs from a theoretical distribution.

• Tests of independence

A test of independence assesses whether paired observations on two variables, expressed in a contingency table, are independent of each other.

By
Siddhartha Srinivas Ippaka