Pearson's chi | chi square approximation
evaluateshowlikelyitisthatanydifferencebetweendatasetsarosebychancePearsonschi-squaredtest(χ2{displaystylechi{2}})isastatisticaltestappliedtosetsofcategoricaldatatoevaluatehowlikelyitisthatanyobserveddifferencebetweenthesetsarosebychance.Itisthemostwidelyusedofmanychi-squaredtests(e.g.,Yates,likelihoodratio,portmanteautestintimeseries,etc.)–statisticalprocedureswhoseresultsareevaluatedbyreferencetothechi-squareddistribution.ItspropertieswerefirstinvestigatedbyKarlPearsonin1900.[1]Incontextsw...
evaluates how likely it is that any difference between data sets arose by chance
Pearsons chi-squared test (χ2{displaystyle chi {2}}) is a statistical test applied to sets of categorical data to evaluate how likely it is that any observed difference between the sets arose by chance. It is the most widely used of many chi-squared tests (e.g., Yates, likelihood ratio, portmanteau test in time series, etc.) – statistical procedures whose results are evaluated by reference to the chi-squared distribution. Its properties were first investigated by Karl Pearson in 1900.[1] In contexts where it is important to improve a distinction between the test statistic and its distribution, names similar to Pearson χ-squared test or statistic are used.
It tests a null hypothesis stating that the frequency distribution of certain events observed in a sample is consistent with a particular theoretical distribution. The events considered must be mutually exclusive and have total probabi...