The employment percentages for men versus women in a computer company last year were 80% and 40%, respectively. At the beginning of this year, they had 150 men and 60 women currently hired. The owner of the company wishes to check their hiring practices and ensure that the percentages have not changed.

1. What is an appropriate alternative hypotheses?
2. What is appropriate test value for the hypotheses?
3. What is the appropriate critical value for this test at the .05 level?

1. The appropriate alternative hypothesis is that the employment percentages for men and women have changed, indicating possible bias in the hiring practices of the computer company.

2. To test the hypothesis, we can calculate the employment percentages for men and women at the beginning of this year and compare them to the percentages from last year.

To calculate the employment percentages, we divide the number of employees of each gender by the total number of employees.

For men:
Percentage of men = (Number of men / Total number of employees) * 100
= (150 / (150 + 60)) * 100
= 71.43%

For women:
Percentage of women = (Number of women / Total number of employees) * 100
= (60 / (150 + 60)) * 100
= 28.57%

3. To determine the appropriate critical value for the hypothesis test, we need to use a significance level or alpha value. In this case, the significance level is given as 0.05 or 5% (the .05 level).

Since the hypothesis is comparing two proportions, we need to perform a two-proportion z-test.

The critical value for a two-sided z-test at the 0.05 level is approximately ±1.96. This means that if the test statistic falls outside the range of -1.96 to +1.96, we can reject the null hypothesis and conclude that there is evidence of a change in the employment percentages.