a sociologist claims the probability that a person picked at random in times square in new york city is visiting the area is 0.63. you want to test to see if the proportion is actually higher. a. identify the null and alternative hypotheses. ( h_0 ) : select an answer? ( h_a ) : select an answer? identify the type i error. you decide that the proportion of people in times square who are visiting is not 0.63, when, in reality, the proportion of people in times square who are visiting is not 0.63. you decide that the proportion of people in times square who are visiting is not 0.63, when, in reality, the proportion of people in times square who are visiting is 0.63. you decide that the proportion of people in times square who are visiting is 0.63, when, in reality, the proportion of people in times square who are visiting is 0.63. you decide that the proportion of people in times square who are visiting is 0.63, when, in reality, the proportion of people in times square who are visiting is not 0.63. identify the type ii error. you decide that the proportion of people in times square who are visiting is not 0.63, when, in reality, the proportion of people in times square who are visiting is not 0.63. you decide that the proportion of people in times square who are visiting is not 0.63, when, in reality, the proportion of people in times square who are visiting is 0.63. you decide that the proportion of people in times square who are visiting is 0.63, when, in reality, the proportion of people in times square who are visiting is 0.63. you decide that the proportion of people in times square who are visiting is 0.63, when, in reality, the proportion of people in times square who are visiting is not 0.63.

Question

a sociologist claims the probability that a person picked at random in times square in new york city is visiting the area is 0.63. you want to test to see if the proportion is actually higher. a. identify the null and alternative hypotheses. ( h_0 ) : select an answer?  ( h_a ) : select an answer? identify the type i error. you decide that the proportion of people in times square who are visiting is not 0.63, when, in reality, the proportion of people in times square who are visiting is not 0.63. you decide that the proportion of people in times square who are visiting is not 0.63, when, in reality, the proportion of people in times square who are visiting is 0.63. you decide that the proportion of people in times square who are visiting is 0.63, when, in reality, the proportion of people in times square who are visiting is 0.63. you decide that the proportion of people in times square who are visiting is 0.63, when, in reality, the proportion of people in times square who are visiting is not 0.63. identify the type ii error. you decide that the proportion of people in times square who are visiting is not 0.63, when, in reality, the proportion of people in times square who are visiting is not 0.63. you decide that the proportion of people in times square who are visiting is not 0.63, when, in reality, the proportion of people in times square who are visiting is 0.63. you decide that the proportion of people in times square who are visiting is 0.63, when, in reality, the proportion of people in times square who are visiting is 0.63. you decide that the proportion of people in times square who are visiting is 0.63, when, in reality, the proportion of people in times square who are visiting is not 0.63.

Accepted Answer

# Brief Explanations:
- **Null and Alternative Hypotheses**:
    - The null hypothesis $H_0$ is a statement of no effect or no difference. Here, it should be that the proportion $p$ of people visiting Times Square is $0.63$, so $H_0:p = 0.63$.
    - The alternative hypothesis $H_A$ is what we are testing for. Since we want to test if the proportion is higher, $H_A:p>0.63$.
 - **Type - I Error**:
    - A Type - I error occurs when we reject the null hypothesis $H_0$ when it is actually true. In this context, we reject $H_0:p = 0.63$ (i.e., we decide the proportion is not $0.63$) when in reality $p = 0.63$.
 - **Type - II Error**:
    - A Type - II error occurs when we fail to reject the null hypothesis $H_0$ when it is actually false. Here, we fail to reject $H_0:p = 0.63$ (i.e., we decide the proportion is $0.63$) when in reality $p
eq0.63$.

# Answer:
- $H_0:p = 0.63$, $H_A:p>0.63$
- Type I error: You decide that the proportion of people in Times Square who are visiting is NOT $0.63$, when, in reality, the proportion of people in Times Square who are visiting is $0.63$
- Type II error: You decide that the proportion of people in Times Square who are visiting is $0.63$, when, in reality, the proportion of people in Times Square who are visiting is NOT $0.63$

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