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1. what claim abojt a proportion from the article did we test 2. what was our bull hypothesis for the proportion 3. what was the alternative hypothesis for the proportion

It seems you've uploaded a screenshot related to a statistics assignment involving descriptive statistics, confidence intervals, and hypothesis testing. However, I cannot directly identify the specific article or proportion claim being referenced without additional context from the text.

To answer your three questions:

1. **What claim about a proportion from the article did we test?**  
   To address this, I would need to know the specific proportion or claim made in the article you're working with. For example, in hypothesis testing, typical claims involve proportions of a population (e.g., "50% of students are over 25 years old").

2. **What was our null hypothesis for the proportion?**  
   In hypothesis testing for proportions, the **null hypothesis** (denoted as \( H_0 \)) usually states that the proportion is equal to a specific value. For instance, \( H_0: p = p_0 \), where \( p_0 \) is the claimed population proportion.

3. **What was the alternative hypothesis for the proportion?**  
   The **alternative hypothesis** (denoted as \( H_a \)) states that the proportion is different from the null hypothesis value. Depending on the test, the alternative hypothesis could take three forms:
   - \( H_a: p \neq p_0 \) (two-tailed test),
   - \( H_a: p > p_0 \) (right-tailed test),
   - \( H_a: p < p_0 \) (left-tailed test).

To provide more specific answers, could you clarify or provide further details from the article or assignment?

Would you like to discuss more details or specific questions? Here are five follow-up questions that might help:

1. What is the proportion value mentioned in the article?
2. Is the hypothesis test one-tailed or two-tailed?
3. What data is used to support or refute the claim from the article?
4. How is the sample size related to the hypothesis test?
5. Have you calculated a p-value or test statistic for the proportion?

**Tip:** Always clearly define your null and alternative hypotheses before conducting a test to avoid confusion during interpretation.

1. What claim about a proportion from the article did we test? 2. What was our null hypothesis for the proportion? 3. What was the alternative hypothesis for the proportion?

Learn about hypothesis testing for proportions, including null and alternative hypotheses. This explanation covers key concepts like sample proportion, the z-test formula for proportions, and the Central Limit Theorem, making it suitable for college-level statistics students.

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