Less than 87% of workers indicate that they are mildly dissatisfied with their job. Express the null and alternative hypotheses in symbolic form for this claim (enter as a percentage).

Use the following codes to enter the following symbols:
enter >=
enter <=
enter !=

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.

Less than 87% of workers indicate that they are mildly dissatisfied with their job. Express the null and alternative hypotheses in symbolic form for this claim (enter as a percentage).

Understand how to express the null and alternative hypotheses for a claim involving job satisfaction proportions. This problem focuses on hypothesis testing for population proportions, specifically when less than 87% of workers are mildly dissatisfied. Suitable for undergraduate students learning statistics.

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