Definition:Chi-Squared Test/Lack of Association
Jump to navigation
Jump to search
Definition
Let $C$ be a contingency table with $r$ rows and $c$ columns.
The expected number in an arbitrary cells can be calculated from the fixed marginal totals.
A statistic in the form $\chi^2$ as defined in $\chi$-squared test for goodness of fit can be calculated by taking all the observed and expected numbers in each cell and summing over all cells.
The number of degrees of freedom is $\paren {r - 1} \paren {c - 1}$
Large values of $\chi^2$ indicate rejection of the hypothesis that the numbers in the cells are independent.
 | This article is complete as far as it goes, but it could do with expansion. In particular: Expand this with further details You can help $\mathsf{Pr} \infty \mathsf{fWiki}$ by adding this information. To discuss this page in more detail, feel free to use the talk page. When this work has been completed, you may remove this instance of {{Expand}} from the code.If you would welcome a second opinion as to whether your work is correct, add a call to {{Proofread}} the page. |
Also see
- Results about the $\chi$-squared test can be found here.
Sources
- 1998: David Nelson: The Penguin Dictionary of Mathematics (2nd ed.) ... (previous) ... (next): chi-squared test: 2.
- 2008: David Nelson: The Penguin Dictionary of Mathematics (4th ed.) ... (previous) ... (next): chi-squared test: 2.