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In this question, you're asked to determine what type of hypothesis test is being performed based on the given null and alternative hypotheses:

- Null Hypothesis (\( H_0 \)): \( p = 0.43 \)
- Alternative Hypothesis (\( H_1 \)): \( p < 0.43 \)

### Explanation:
- The null hypothesis (\( H_0 \)) is a statement of no effect or no difference, which is \( p = 0.43 \).
- The alternative hypothesis (\( H_1 \)) suggests that the population proportion \( p \) is less than 0.43.

Since the alternative hypothesis uses a "less than" (\( < \)) symbol, this indicates that you are testing whether the parameter is less than a certain value. Therefore, this is a **left-tailed test** because you're only concerned with the lower side of the distribution.

### Answer: 
The correct option is **left-tailed**.

Would you like more details on hypothesis testing? Here are some related questions you might find useful:

1. What is the difference between one-tailed and two-tailed tests?
2. How do you interpret p-values in hypothesis tests?
3. When should you use a left-tailed vs. right-tailed test?
4. How does the significance level (\( \alpha \)) affect hypothesis testing?
5. What are Type I and Type II errors in hypothesis testing?

**Tip**: For left-tailed tests, the critical region is on the left side of the distribution, where you expect values smaller than the hypothesized parameter value.

If the null and alternative hypotheses are: H0: p = 0.43, H1: p < 0.43, what kind of test is this?

Learn how to determine the type of hypothesis test for the given null hypothesis H0: p = 0.43 and alternative hypothesis H1: p < 0.43. This problem involves one-tailed hypothesis testing with a focus on proportions, suitable for Grades 11-12 or introductory college students.

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