91影视

Given that

The expected table is

The following conditions must be met in order to use the chi-square test: - Two categorical variables.

- Each variable has two or more categories.

- Observation independence - Expected frequency for each cell is at least 1 or should be at least 5 for the majority (80%) of the cells.

Because the given information satisfies each condition. As a result, the chi-square test can be applied to the given dataset.

$\text{The test statistics is}24.8978.$

$df=(n-1)(m-1)$

$p-\text{value}=P\left({蠂}^2>{蠂}_{\text{text}}^2\right)$

$df=(4-1)(2-1)$

$df=(4-1)(2-1)$

= 3

There is the following commend to find p-value on TI83,

$"{蠂}^{2}cdf(24.8978,99,3)"$

The output is,

localid="1653293946609" $\text{Sothe p-value is}0.1621759222\mathrm{E}-5\text{.}$

$H_0:\left(\begin{array}{l}\text{There is no difference in the distribution sports goals}\\ \text{for male and female undergraduates at the university}\end{array}\right)$

$H_1:\left(\begin{array}{l}\text{There is a difference in the distribution sports goals}\\ \text{for male and female undergraduates at the university}\end{array}\right)$

If the null hypothesis is true, the p-value represents the probability of obtaining results that are as extreme as the test statistic value. If there is no relationship between gender and sports goal, the likelihood of getting a sample as extreme or more extreme than the given sample is$0.1621759222E-5.$

When the $p$value is less than the level of significance, the null hypothesis is rejected.

In this case, the$p$value is less than the level of significance. As a result, the null hypothesis is rejected.

As a result, there is enough evidence to conclude that there is a relationship between the variables goal and sex.