To express the null and alternative hypotheses in symbolic form, we define $p$ as the proportion of workers who indicate that they are mildly dissatisfied with their job.

The hypotheses are as follows:

• Null hypothesis $H_0$: The proportion of workers who are mildly dissatisfied is greater than or equal to 87%. $H_0: p \geq 87\%$

• Alternative hypothesis $H_1$: The proportion of workers who are mildly dissatisfied is less than 87%. $H_1: p < 87\%$

Would you like a detailed explanation of hypothesis testing or have any other questions?

Here are five related questions:

1. What are the key steps in conducting a hypothesis test for population proportions?
2. How do you calculate the test statistic for a proportion hypothesis test?
3. What is the significance level ($\alpha$) in hypothesis testing?
4. How is the p-value interpreted in hypothesis testing?
5. What is the difference between a one-tailed and two-tailed test?

Tip: Always clearly define the parameter of interest (like the proportion $p$) before formulating hypotheses.