You have reason to believe that there are actually more raisins in each box than the company claims. Your alternative hypothesis, \( H_{a} \), would be \( \mu<200 \) \( \mu>200 \) \( \mu=200 \) \( \mu \neq 200 \)

In your case, if you suspect that the company is underselling and there are more raisins than claimed, your alternative hypothesis \( H_{a} \) would be \( \mu > 200 \). This indicates you believe the average number of raisins per box is greater than the stated amount. On the flip side, if you're convinced that the company is misleading about the raisin count by claiming more than they actually provide, then your alternative hypothesis might be \( H_{a} \) like \( \mu < 200 \). Remember, hypotheses help guide your statistical testing and choosing the right one is crucial for your research outcome.