Why do we reject a chi-square statistic when the p-value to the right is larger?
I would like to understand why, instead of just following steps given.
Given that we calculate the chi-square statistic (A), and comparing it against the test statistic for the given significance level (B), we reject null hypothesis if the A is higher than B.
However, this is where I'm a little confused. Given an example where $alpha = 0.05$ for instance, if my test statistic (A) is smaller, that means that the area to the right ($alpha$) is larger than 0.05.
In other words, the probability of a Type I error is higher than 0.05. Hence, shouldn't we be rejecting the null hypothesis when A is smaller than B instead?
probability hypothesis-testing
asked Nov 23 at 6:07
statsguy21
858
add a comment |
I would like to understand why, instead of just following steps given.
Given that we calculate the chi-square statistic (A), and comparing it against the test statistic for the given significance level (B), we reject null hypothesis if the A is higher than B.
However, this is where I'm a little confused. Given an example where $alpha = 0.05$ for instance, if my test statistic (A) is smaller, that means that the area to the right ($alpha$) is larger than 0.05.
In other words, the probability of a Type I error is higher than 0.05. Hence, shouldn't we be rejecting the null hypothesis when A is smaller than B instead?
probability hypothesis-testing
asked Nov 23 at 6:07
statsguy21
858
add a comment |
I would like to understand why, instead of just following steps given.
Given that we calculate the chi-square statistic (A), and comparing it against the test statistic for the given significance level (B), we reject null hypothesis if the A is higher than B.
However, this is where I'm a little confused. Given an example where $alpha = 0.05$ for instance, if my test statistic (A) is smaller, that means that the area to the right ($alpha$) is larger than 0.05.
In other words, the probability of a Type I error is higher than 0.05. Hence, shouldn't we be rejecting the null hypothesis when A is smaller than B instead?
probability hypothesis-testing
asked Nov 23 at 6:07
statsguy21
858
I would like to understand why, instead of just following steps given.
Given that we calculate the chi-square statistic (A), and comparing it against the test statistic for the given significance level (B), we reject null hypothesis if the A is higher than B.
However, this is where I'm a little confused. Given an example where $alpha = 0.05$ for instance, if my test statistic (A) is smaller, that means that the area to the right ($alpha$) is larger than 0.05.
In other words, the probability of a Type I error is higher than 0.05. Hence, shouldn't we be rejecting the null hypothesis when A is smaller than B instead?
probability hypothesis-testing
probability hypothesis-testing
asked Nov 23 at 6:07
statsguy21
858
asked Nov 23 at 6:07
statsguy21
858
asked Nov 23 at 6:07
statsguy21
858
asked Nov 23 at 6:07
statsguy21
858
asked Nov 23 at 6:07
statsguy21
858
858
add a comment |
add a comment |
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