H-Hypothesis (Chi Square Test)

Injury type is independent of position played

Injury type is dependent on the position played independent

The distribution of political views this year is 0.24 liberal, 0.38 moderate, 0.38 conservative.

The distribution of political views this year differs from a distribution of 0.24 liberal, 0.38 moderate, 0.38 conservative.

The distribution of political views this year is independent of gender.

This is not a situation where using a Chi-Square Goodness of Fit Test is appropriate.

The null hypothesis is that the closer students get to graduation, the less likely they are to be opposed to tuition increases.  The alternative is that how close students are to graduation makes no difference in their opinion.

The null hypothesis is that the mean number of students who are strongly opposed is the same for each of the 4 years.  The alternative is that the mean is different for at least 2 of the 4 years.

The null hypothesis is that the distribution of student opinion about the proposed tuition increase is the same for each of the 4 years at the university.  The alternative is that the distribution is different for at least 2 of the 4 years.

The null hypothesis is that year in school and student opinion about the tuition increase in the sample are independent.  The alternative is that these variables are dependent.

There is a relation between the schools and the grade of Mathematics.

There is no relation between the schools and the grade of Mathematics.

There is an association between the schools and the grade of Mathematics.

The schools and grade of Mathematics are not independent.

There is a relationship between the schools and the grade of Mathematics.

There is no relationship between the schools and the grade of Mathematics.

There is no association between the schools and the grade of Mathematics.

The schools and grade of Mathematics are independent.

The null hypothesis is not relevant in a chi square test.

The null hypothesis is based on continuous data rather than categorical data.

There is no significant difference between the observed and expected frequencies of the categorical data.

The null hypothesis states that there is a significant difference between the observed and expected frequencies.

The alternative hypothesis states that there is a significant difference in student opinions based on their year in school.

The alternative hypothesis states that student opinions are independent of their year in school.

The alternative hypothesis states that all students are equally opposed to the tuition increase.

The alternative hypothesis states that the distribution of opinions is the same across all years.

It means there is no significant difference between the observed and expected frequencies.

It means there is a significant difference between the observed and expected frequencies.

It means the data is not suitable for a chi-square test.

It means the sample size is too small to draw conclusions.

To determine if there is a significant association between two categorical variables.

To compare means between two groups.

To assess the relationship between a continuous variable and a categorical variable.

To evaluate the variance within a single categorical variable.