From the image you provided, we have a hypothesis testing problem regarding the proportion of female fish in a population. The claim is that "at most 54% are female," and a test is being conducted to evaluate this claim.

Hypotheses Setup:

• Null Hypothesis (H₀): This represents the claim that the proportion of female fish is at most 54%. Mathematically, this is stated as: $H_0: p \leq 0.54$

• Alternative Hypothesis (H₁ or Hₐ): This is the hypothesis that challenges the null. Since the test is about whether the proportion is greater than 54%, the alternative hypothesis is: $H_a: p > 0.54$

Thus, you should fill in the boxes as follows:

• Null Hypothesis (H₀): $p \leq 0.54$
• Alternative Hypothesis (H₁): $p > 0.54$

Do you need further clarification or details on hypothesis testing or the process of setting these up?

Here are 5 relative questions for further practice:

1. What is the difference between a one-tailed and a two-tailed hypothesis test?
2. How do you determine the appropriate significance level (α) for a hypothesis test?
3. What is a Type I error in hypothesis testing, and how can it be minimized?
4. How do you calculate the test statistic for a proportion hypothesis test?
5. When should you use a z-test for proportions?

Tip: In hypothesis testing, always carefully distinguish between the null and alternative hypotheses, especially in one-tailed tests, to ensure your conclusions align with the initial claim.