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The null hypothesis is shown below:

$H_0$: The salary is independent of the level of education an individual has.

Against the alternative hypothesis as shown below:

$H_a$: The salary is dependent of the level of education an individual has.

The degrees of freedom can be calculated by the formula given below:

$df=(numberofcolumns-1)(numberofrows-1)$

Therefore,

$df=(numberofcolumns-1)(numberofrows-1)$

$=(4-1)(5-1)$

$=3脳4$

$=12$

From the above calculation, it is clear that the distribution for the test is ${蠂}_{12}^2$.

The observed value table is already given in the textbook. Calculate the expected frequencies by using the formula shown below:

$E=\frac{\text{(row total}\left)\right(\text{column total})}{\text{overall total}}$

All calculations can be done in excel worksheet. Hence, the expected$\left(E\right)$values table is shown below:

The test statistic of independence test is given below:

$Teststatistic=\underset{(i脳j)}{鈭�}\frac{(O-E{)}^2}{E}$

To calculate $\frac{(O-E{)}^2}{E}$apply formula $=\left((B4-B14{)}^2\right)/B14$in cell B21 and drag the same formula up to cell F24. After that, take total of columns total and rows total. The table of the test statistic is shown below:

Hence, the test statistic is $255.77$.

The $p$-value can be calculated in excel by using CHIDIST ( ) formula as shown below:

Hence, the$p$- value is$0.000$

Chi-square sketch is given below:

Alpha:$0.05$

Decision: Reject the null hypothesis $H_0$

Reason for decision: Because$p-value<伪$

Conclusion: There is sufficient evidence to ensure that the salary is dependent of the level of education an individual has.