True about chi-square test-
Ans. is 'd' i.e., Used when there are more than 2 group Chi-square test* It is a non-parametric test to measure the association between two or more qualitative variables, i.e. when observations are in proportions, percentage or fractions. It tests the significance of difference between two proportions. As with all non-parametric tests, it is used for non-Normal (non-Gaussian) distribution.* The chi square test has an added advantage. It can be applied to find association or relationship between two discrete attributes when there are more than two class orgroupsas happens in multinomial samples.* Studies often collect data on categorial (qualitative) variables that can be summarized as a series of counts. These counts are commonly arranged in a tubular format known as a contingency table. For example, a study designed to determine whether or not there is association between cigarette smoking and asthma attack might collect data that could be assembled into a 2-2 table - table containing two columns and two rows.* The chi - square test can be used to evaluate whether there is an association between the rows and columns in a contingeny table i.e. between two variables (smoking and asthma attack).* The chi square test assumes that no association occurs between two events in question unless proved otherwise - Null hypothesis. The chi-sequare test is designed to test the null hypothesis which says that there is no association betweens two variables (the rows and columns of a contigency table).* Chi-square test only tells about the presence or absence of association, but it dose not measure the strength of association.Degree of freedom* Degree of freedom is the number of observations in the final calculation that are free to vary. The number of degree of freedom of contigency table is the product of one less the number ofrows(r) and one less the number of column(c).DOF = (C-l) (r-1)* For example in a contigency table with 4 rows and 4 columns, DOF is 9 (4-1 x 4-1 )Contingency tableDegree of freedom (dof)2 x 2 table(2 - 1) (2 - 1) = 13 x 3 table(3 - 1) (3 - 1) = 44 x 4 table(4 - 1) (4 - 1) = 95 x 5 table(5 - 1) (5 - 1) = 163 x 4 table(3 - 1) (4 - 1) = 610 x 20 table(10 - 1) (20 - 1) = 171* The categories defining rows and columns of contigency table must be mutually exclusive.* Yates correction : If there is difference between calculated and theoretical values of chi-square test, this can be compensated by Yates's correction.
Parametric test
Used for Gaussian distribution
Measure the strength of association
Used when there are more than 2 group
Biostatistics