22. To create the following data we started with the same sample means and variances that appeared in problem 21 but doubled the sample size to n 10. Treatment

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**Exercise 22 Explanation for Educational Website:**

This exercise involves modifying data from a previous problem (Problem 21) by doubling the sample size to \( n = 10 \) while keeping the same sample means and variances. The task is to analyze how this change impacts the F-ratio using ANOVA. The data is presented in a table divided into three treatments (I, II, and III).

**Table Layout:**

- Each treatment has the following parameters:
  - **n**: Sample size \( (n = 10) \)
  - **M**: Sample mean
  - **T**: Total sum of scores in the treatment
  - **s²**: Sample variance
  - **SS**: Sum of squares for the treatment

**Treatment Details:**

- **Treatment I:**
  - \( n = 10 \)
  - \( M = 1 \)
  - \( T = 10 \)
  - \( s² = 9.00 \)
  - \( SS = 81 \)

- **Treatment II:**
  - \( n = 10 \)
  - \( M = 5 \)
  - \( T = 50 \)
  - \( s² = 10.00 \)
  - \( SS = 90 \)

- **Treatment III:**
  - \( n = 10 \)
  - \( M = 6 \)
  - \( T = 60 \)
  - \( s² = 11.00 \)
  - \( SS = 99 \)

**Overall Data:**

- Total sum of all treatments (\( \Sigma X² = 890 \))
- \( N = 30 \) (Total number of data points across all treatments)
- Grand total (\( G = 120 \))

**Exercise Requirement:**

a. **Prediction and Analysis:**
   - Predict how increasing the sample size affects the F-ratio for these data compared to the values from Problem 21.
   - Use an ANOVA with \( \alpha = 0.05 \) to test this prediction.
   - Note: Since the samples are of the same size, \( MS_{within} \) (Mean Square Within) is the average of the three sample variances.

This exercise provides a hands-on understanding of how sample size influences statistical analysis using the ANOVA method.
Transcribed Image Text:**Exercise 22 Explanation for Educational Website:** This exercise involves modifying data from a previous problem (Problem 21) by doubling the sample size to \( n = 10 \) while keeping the same sample means and variances. The task is to analyze how this change impacts the F-ratio using ANOVA. The data is presented in a table divided into three treatments (I, II, and III). **Table Layout:** - Each treatment has the following parameters: - **n**: Sample size \( (n = 10) \) - **M**: Sample mean - **T**: Total sum of scores in the treatment - **s²**: Sample variance - **SS**: Sum of squares for the treatment **Treatment Details:** - **Treatment I:** - \( n = 10 \) - \( M = 1 \) - \( T = 10 \) - \( s² = 9.00 \) - \( SS = 81 \) - **Treatment II:** - \( n = 10 \) - \( M = 5 \) - \( T = 50 \) - \( s² = 10.00 \) - \( SS = 90 \) - **Treatment III:** - \( n = 10 \) - \( M = 6 \) - \( T = 60 \) - \( s² = 11.00 \) - \( SS = 99 \) **Overall Data:** - Total sum of all treatments (\( \Sigma X² = 890 \)) - \( N = 30 \) (Total number of data points across all treatments) - Grand total (\( G = 120 \)) **Exercise Requirement:** a. **Prediction and Analysis:** - Predict how increasing the sample size affects the F-ratio for these data compared to the values from Problem 21. - Use an ANOVA with \( \alpha = 0.05 \) to test this prediction. - Note: Since the samples are of the same size, \( MS_{within} \) (Mean Square Within) is the average of the three sample variances. This exercise provides a hands-on understanding of how sample size influences statistical analysis using the ANOVA method.
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