The problem asks for a hypothesis test to determine if the percentage of smokers has reduced after the implementation of smoking cessation programs, based on the previous estimate of 35%.

In hypothesis testing, we define the null hypothesis $H_0$ and the alternative hypothesis $H_a$.

1. Null Hypothesis ($H_0$): This is the hypothesis that there is no change or effect. In this case, the null hypothesis is that the percentage of smokers is still 35%, so: $H_0: p = 0.35$

2. Alternative Hypothesis ($H_a$): This is the hypothesis that reflects the research question. Since you believe that the percentage has reduced, the alternative hypothesis should be: $H_a: p < 0.35$

So, for the drop-down options:

• For $H_0$, select $=$ and 0.35.
• For $H_a$, select $<$ and 0.35.

Do you need further details on the steps involved in hypothesis testing or have any questions?

Here are some related questions:

1. What is the next step in conducting this hypothesis test after setting the hypotheses?
2. How do we determine the significance level ($\alpha$) for the test?
3. What kind of data do we need to perform this test (e.g., sample size, proportion)?
4. What is a one-tailed test, and why is it relevant here?
5. How do we calculate the test statistic for this hypothesis test?

Tip: Always clearly define your hypotheses before performing any hypothesis test, as it sets the stage for the entire analysis.