6. A normal distribution has a mean of µ = 60 and o = 18. For each of the following samples, compute the z-score for the sample mean (M) and indicate whether the sample mean for sample is a typical, representative value or an extreme value for a sample of this size. a. M=67 for n=D4 scores b. M-67 for n= 36 scores

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**Problem 6: Normal Distribution Analysis**

A normal distribution has a mean (\(\mu\)) of 60 and a standard deviation (\(\sigma\)) of 18. For each of the following samples, compute the z-score for the sample mean (M), and indicate whether the sample mean is a typical, representative value or an extreme value for a sample of this size.

a. \(M = 67\) for \(n = 4\) scores  
b. \(M = 67\) for \(n = 36\) scores

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**Instructions:**

1. **Calculate the Standard Error (SE):**  
   The standard error is calculated as \(\sigma / \sqrt{n}\).

2. **Compute the Z-score:**  
   The z-score is calculated as \((M - \mu) / \text{SE}\).

3. **Interpret the Z-score:**  
   Determine if the sample mean is typical or extreme by considering the magnitude of the z-score.

---

This exercise helps in understanding the concept of sampling distribution and the interpretation of z-scores in the context of normal distribution.
Transcribed Image Text:**Problem 6: Normal Distribution Analysis** A normal distribution has a mean (\(\mu\)) of 60 and a standard deviation (\(\sigma\)) of 18. For each of the following samples, compute the z-score for the sample mean (M), and indicate whether the sample mean is a typical, representative value or an extreme value for a sample of this size. a. \(M = 67\) for \(n = 4\) scores b. \(M = 67\) for \(n = 36\) scores --- **Instructions:** 1. **Calculate the Standard Error (SE):** The standard error is calculated as \(\sigma / \sqrt{n}\). 2. **Compute the Z-score:** The z-score is calculated as \((M - \mu) / \text{SE}\). 3. **Interpret the Z-score:** Determine if the sample mean is typical or extreme by considering the magnitude of the z-score. --- This exercise helps in understanding the concept of sampling distribution and the interpretation of z-scores in the context of normal distribution.
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