In populations, tests {chi square} can show whether one property, such as treatments, affects another property, such as recovery level. Properties have mutually exclusive outcomes, such as cured or not.
process
Hypothesize that events are independent. Select significance level, typically 5%. Make contingency table.
Calculate degrees of freedom: (R - 1) * (C - 1), where R is number of table rows and C is number of table columns.
Calculate chi square value: X = sum from i = 1 to i = R and from j = 1 to j = C of (x(i,j) - f(i,j))^2 / f(i,j), where x(i,j) is observed frequency and f(i,j) is expected frequency. f(i,j) = (sum from i = 1 to i = R of x(i,j)) * (sum from j = 1 to j = C of x(i,j)) / (sum from i = 1 to i = R and from j = 1 to j = C of x(i,j)), where x(i,j) is observed frequency.
result
If calculated chi square value is less than actual chi square value for degrees of freedom at significance level, do not reject hypothesis.
Mathematical Sciences>Statistics>Tests
Outline of Knowledge Database Home Page
Description of Outline of Knowledge Database
Date Modified: 2022.0224