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.