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The question in the image involves identifying the type of hypothesis test based on the null and alternative hypotheses.

Given:
- \( H_0: p = 0.82 \) (The null hypothesis, where \( p \) is equal to 0.82)
- \( H_1: p > 0.82 \) (The alternative hypothesis, suggesting \( p \) is greater than 0.82)

Since the alternative hypothesis \( H_1 \) is stating that \( p \) is greater than 0.82, this indicates a **right-tailed** test. A right-tailed test is used when the alternative hypothesis is checking for values greater than the null hypothesis.

So, the correct answer is **right-tailed**.

Would you like more details or have any further questions?

Here are five related questions to explore further:
1. What are the key differences between left-tailed, right-tailed, and two-tailed tests?
2. How is the critical region defined in a right-tailed test?
3. What conditions justify choosing a right-tailed test over a two-tailed test?
4. How do you calculate the p-value for a right-tailed test?
5. In which situations would a two-tailed test be preferred?

**Tip:** When determining the direction of the hypothesis test, always focus on the inequality in the alternative hypothesis.

If the null and alternative hypotheses are H₀: p = 0.82 and H₁: p > 0.82, what type of hypothesis test is it?

Learn how to determine the type of hypothesis test (left-tailed, right-tailed, or two-tailed) by analyzing the null and alternative hypotheses. Example: H₀: p = 0.82, H₁: p > 0.82 is a right-tailed test.

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