BACHELOR OF BUSINESS ADMINISTRATION

Detailed explanation-1: -For a Chi-square test, a p-value that is less than or equal to your significance level indicates there is sufficient evidence to conclude that the observed distribution is not the same as the expected distribution. You can conclude that a relationship exists between the categorical variables.

Detailed explanation-2: -P > 0.05 is the probability that the null hypothesis is true. 1 minus the P value is the probability that the alternative hypothesis is true. A statistically significant test result (P ≤ 0.05) means that the test hypothesis is false or should be rejected. A P value greater than 0.05 means that no effect was observed.

Detailed explanation-3: -Greater differences between expected and actual data produce a larger Chi-square value. The larger the Chi-square value, the greater the probability that there really is a significant difference.

Detailed explanation-4: -If the observed chi-square test statistic is greater than the critical value, the null hypothesis can be rejected.