Boyd_​BA 310_​Ch. 8-9 HW

Test 1:

Null Hypothesis- The average monthly income of our company's employees is equal to the national average of $6,200.

Alternative Hypothesis- The average monthly income of our company's employees is not equal to the national average of $6,200.

The sample mean of the monthly income for our cleaned dataset is $6,200.

The p-value for this two-tail test is 0.

We reject the null hypothesis.

Response to the CEO- Based on our data, our compensation levels are significantly different from the industry baseline. We should investigate whether we are appropriately paying compared to the national average to ensure we remain competitive while also being cost effective.

Test 2:

Null Hypothesis- The company's attrition proportion is less than or equal to the industry baseline (p<=0.12)

Alternative Hypothesis- The company's attrition proportion is significantly greater than the industry baseline (p>0.12)

The sample proportion of attrition is 0.171 or 17.1%.

The calculated one-tail p-value is 0/2= 0.

We reject the null hypothesis because the calculated one-tail p-value is below the significance level.

Test 3:

Null Hypothesis- Attrition and Department are independent (Department does not affect leaving).

Alternative Hypothesis- Attrition and Department are dependent (Department affects leaving).

The highest count of "Yes" for Attrition was Research & Development.

The test statistics:

• Degrees of Freedom = 2

• Chi-Square Statistic = ~14.2

• Exact p-value = ~.0008

We reject the hypothesis because there is a relationship between an employee's department and their likelihood of leaving. Attrition is not evenly distributed across the company.