Find the error margin for a 98% confidence interval for the average value of Y when X is 9. ### Summary of Statistical Analysis**Summations:**- $\Sigma x = 210$- $\Sigma x^2 = 2870$- $\Sigma xy = -10745$**Summations for $y$:**- $\Sigma y = -759$- $\Sigma y^2 = 62523$**Regression Equation:**\[ y = 5.873684 - 4.173684x \]### ANOVA Table for Regression Analysis:| Source | SS | df | MS | F ||--------------|-------------|----|-------------|----------|| Regression | 11548.06053 | 1 | 11584.06053 | 9.42011 || Error | 22134.88947 | 18 | 1229.716 | || **Total** | 33718.95 | 19 | | |- **SS** (Sum of Squares) indicates the variability.- **df** (degrees of freedom) reflects the number of values free to vary.- **MS** (Mean Square) is calculated by dividing SS by df.- **F** is the F-ratio for determining the significance of the regression.This table and the regression equation provide a basis for analyzing the relationship between the dependent and independent variables, indicating a significant regression relationship with the given F-value (9.42011).

Given: The error margin for 98% confidence internal for the average value of Y when X is 9

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Find the error margin for a 98% confidence interval for the average value of Y when X is 9.

A First Course in Probability (10th Edition)

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ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

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Estimation

A new framework of data analysis where the new statistical methods are used for interpreting the results and analyzing the data is known as estimation in statistics.

Question

Find the error margin for a 98% confidence interval for the average value of Y when X is 9.

### Summary of Statistical Analysis

**Summations:**
- $\Sigma x = 210$
- $\Sigma x^2 = 2870$
- $\Sigma xy = -10745$

**Summations for $y$:**
- $\Sigma y = -759$
- $\Sigma y^2 = 62523$

**Regression Equation:**
\[ y = 5.873684 - 4.173684x \]

### ANOVA Table for Regression Analysis:

| Source | SS | df | MS | F |
|--------------|-------------|----|-------------|----------|
| Regression | 11548.06053 | 1 | 11584.06053 | 9.42011 |
| Error | 22134.88947 | 18 | 1229.716 | |
| **Total** | 33718.95 | 19 | | |

- **SS** (Sum of Squares) indicates the variability.
- **df** (degrees of freedom) reflects the number of values free to vary.
- **MS** (Mean Square) is calculated by dividing SS by df.
- **F** is the F-ratio for determining the significance of the regression.

This table and the regression equation provide a basis for analyzing the relationship between the dependent and independent variables, indicating a significant regression relationship with the given F-value (9.42011).

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