Assume that we want to construct a confidence interval. Do one of the following, as appropriate: (a) find the critical value ta/2, (b) find the critical value za/2, or ( state that neither the normal distribution nor the t distribution applies. Here are summary statistics for randomly selected weights of newborn girls:n= 226, x = 31.8 hg, s= 7.5 hg. The confidence level is 95%. %3D

MATLAB: An Introduction with Applications
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**Constructing a Confidence Interval**

Assume that we want to construct a confidence interval. You have the following options, as appropriate:

(a) Find the critical value \( t_{\alpha/2} \).

(b) Find the critical value \( z_{\alpha/2} \).

(c) State if neither the normal distribution nor the t distribution applies.

Here are the summary statistics for randomly selected weights of newborn girls:

- \( n = 226 \)
- \( \bar{x} = 31.8 \) hg
- \( s = 7.5 \) hg

The confidence level is 95%.

---

**Explanation:**

In statistics, constructing a confidence interval involves determining the range in which we expect a population parameter to lie. Here, you can decide whether to use the t-distribution or z-distribution based on the given sample size and other criteria. 

1. **\( t_{\alpha/2} \) Critical Value:**
   - Used when the sample size is small (typically \( n < 30 \)) or the population standard deviation is unknown.
   - Appropriate for this example depending on the nature of the population distribution.

2. **\( z_{\alpha/2} \) Critical Value:**
   - Used when the sample size is large (typically \( n \geq 30 \)) and the population standard deviation is known or the sample is drawn from a normally distributed population.
   - Appropriate here since the sample size is large (\( n = 226 \)).

3. **Decision on Distributions:**
   - Assess if the assumptions for normal or t distributions are met. If not, indicate the inapplicability of both.

This process helps in making inferences about the population with a specified level of confidence, here given as 95%.
Transcribed Image Text:**Constructing a Confidence Interval** Assume that we want to construct a confidence interval. You have the following options, as appropriate: (a) Find the critical value \( t_{\alpha/2} \). (b) Find the critical value \( z_{\alpha/2} \). (c) State if neither the normal distribution nor the t distribution applies. Here are the summary statistics for randomly selected weights of newborn girls: - \( n = 226 \) - \( \bar{x} = 31.8 \) hg - \( s = 7.5 \) hg The confidence level is 95%. --- **Explanation:** In statistics, constructing a confidence interval involves determining the range in which we expect a population parameter to lie. Here, you can decide whether to use the t-distribution or z-distribution based on the given sample size and other criteria. 1. **\( t_{\alpha/2} \) Critical Value:** - Used when the sample size is small (typically \( n < 30 \)) or the population standard deviation is unknown. - Appropriate for this example depending on the nature of the population distribution. 2. **\( z_{\alpha/2} \) Critical Value:** - Used when the sample size is large (typically \( n \geq 30 \)) and the population standard deviation is known or the sample is drawn from a normally distributed population. - Appropriate here since the sample size is large (\( n = 226 \)). 3. **Decision on Distributions:** - Assess if the assumptions for normal or t distributions are met. If not, indicate the inapplicability of both. This process helps in making inferences about the population with a specified level of confidence, here given as 95%.
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