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The data is

The null hypothesis states that there is no association between the variables:

$H_0$: There is no difference between the distribution of sports goals for females and the distribution of sports goals for males.

The alternative hypothesis states that there is an association between the variables:

$H_a$: There is a difference between the distribution of sports goals for females and the distribution of sports goals for males.

The data given is

From the given

$n_1=67$

$n_2=67$

localid="1650643199717" $$\begin{gathered} n=67+67 \\ =134 \end{gathered}$$

The expected count is the row total multiplied by the sample size divided by the total sample size $n=134$

The given data is

Observed counts

Expected counts

The chi-square statistic is the sum of squared deviations (between observed and expected counts) divided by the expected count:

$$\begin{gathered} {蠂}^2=\frac{(14-22.5{)}^2}{22.5}+\frac{(7-12.5{)}^2}{12.5}+\frac{(21-13{)}^2}{13}+\frac{(25-19{)}^2}{19}+\frac{(31鈭�22.5{)}^2}{22.5}+\frac{(18鈭�12.5{)}^2}{12.5}+\frac{(5鈭�13{)}^2}{13}+\frac{(13鈭�19{)}^2}{19} \\ 鈮�24.8978 \end{gathered}$$