Chisquare意思

"Chi-square" (χ²) is a statistical term that is used in hypothesis testing, particularly in tests of goodness of fit and tests for independence. It is a measure of how different the observed data is from the data that would be expected if a certain hypothesis were true.

The chi-square statistic is calculated by summing the squared differences between the observed frequencies and the expected frequencies in each cell of a contingency table, and then dividing by the expected frequency. The formula for the chi-square statistic is:

χ² = Σ [(O - E)² / E]

where O is the observed frequency, E is the expected frequency, and the summation is over all cells in the contingency table.

The chi-square distribution is a family of distributions that is used to determine the probability of a chi-square statistic that is a certain value or more extreme. The chi-square distribution is right-skewed and has two parameters: the degrees of freedom (df), which determine the shape of the distribution, and the number of observations (n), which determine the scale of the distribution.

The chi-square distribution is used in hypothesis testing to determine whether the observed data is significantly different from the data that would be expected if the null hypothesis were true. If the chi-square statistic is large, it indicates that the observed data is significantly different from the data that would be expected if the null hypothesis were true, and the null hypothesis is rejected. If the chi-square statistic is not large, it indicates that the observed data is not significantly different from the data that would be expected if the null hypothesis were true, and the null hypothesis is not rejected.