A scientist has read that the mean birth weight of babies born at full term is 7.3 pounds. The scientist has good reason to believe that the mean birth weight of babies born at full term, μ, is less than this value and plans to perform a statistical test. She selects a random sample of birth weights of babies born at full term and finds the mean of the sample to be 6.9 pounds and the standard deviation to be 1.7 pounds. Based on this information, complete the parts below. (a) What are the null hypothesis H and the alternative hypothesis H₁ that should be used for the test? Ho :O H₁:0 (b) Suppose that the scientist decides not to reject the null hypothesis. What sort of error might she be making? (Choose one) ▼ (c) Suppose the true mean birth weight of babies born at full term is 7.3 pounds. Fill in the blanks to describe a Type I error. A Type I error would be (Choose one) the hypothesis that u is (Choose one) (Choose one) when, in fact, μ is (Choose one) H O

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A scientist has read that the mean birth weight of babies born at full term is 7.3 pounds. The scientist has good reason to believe that the mean birth weight of babies born at full term, \( \mu \), is less than this value and plans to perform a statistical test. She selects a random sample of birth weights of babies born at full term and finds the mean of the sample to be 6.9 pounds and the standard deviation to be 1.7 pounds.

Based on this information, complete the parts below.

(a) What are the null hypothesis \( H_0 \) and the alternative hypothesis \( H_1 \) that should be used for the test?

\[
H_0: \boxed{}
\]

\[
H_1: \boxed{}
\]

(b) Suppose that the scientist decides not to reject the null hypothesis. What sort of error might she be making?

(Choose one) \(\longrightarrow\) [Dropdown menu]

(c) Suppose the true mean birth weight of babies born at full term is 7.3 pounds. Fill in the blanks to describe a Type I error.

A Type I error would be (Choose one) \(\longrightarrow\) [Dropdown menu] the hypothesis that \( \mu \) is (Choose one) \(\longrightarrow\) [Dropdown menu]

(Choose one) \(\longrightarrow\) [Dropdown menu] when, in fact, \( \mu \) is (Choose one) \(\longrightarrow\) [Dropdown menu]

**Diagram Explanation:**
To the right of the text, there are several symbols related to statistical testing:

1. \( \mu \) 
2. \(\bar{x} \) 
3. Square boxes with arrows pointing in different directions, representing comparison symbols:
   - \(\leq\)
   - \(>\)
   - \(\geq\)
   - \(<\)
   - \(=\)
   - Example symbols for setting up hypotheses.
Transcribed Image Text:A scientist has read that the mean birth weight of babies born at full term is 7.3 pounds. The scientist has good reason to believe that the mean birth weight of babies born at full term, \( \mu \), is less than this value and plans to perform a statistical test. She selects a random sample of birth weights of babies born at full term and finds the mean of the sample to be 6.9 pounds and the standard deviation to be 1.7 pounds. Based on this information, complete the parts below. (a) What are the null hypothesis \( H_0 \) and the alternative hypothesis \( H_1 \) that should be used for the test? \[ H_0: \boxed{} \] \[ H_1: \boxed{} \] (b) Suppose that the scientist decides not to reject the null hypothesis. What sort of error might she be making? (Choose one) \(\longrightarrow\) [Dropdown menu] (c) Suppose the true mean birth weight of babies born at full term is 7.3 pounds. Fill in the blanks to describe a Type I error. A Type I error would be (Choose one) \(\longrightarrow\) [Dropdown menu] the hypothesis that \( \mu \) is (Choose one) \(\longrightarrow\) [Dropdown menu] (Choose one) \(\longrightarrow\) [Dropdown menu] when, in fact, \( \mu \) is (Choose one) \(\longrightarrow\) [Dropdown menu] **Diagram Explanation:** To the right of the text, there are several symbols related to statistical testing: 1. \( \mu \) 2. \(\bar{x} \) 3. Square boxes with arrows pointing in different directions, representing comparison symbols: - \(\leq\) - \(>\) - \(\geq\) - \(<\) - \(=\) - Example symbols for setting up hypotheses.
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