The exercise involving data in this and subsequent sections were designed to be solved using Excel. The following estimated regression equation is based on 10 observations was presented. ŷ = 29.1270 + 0.5906x1 + 0.4980x Here SST = 6,942.625, SSR = 6,737.375, Sh = 0.0894, and sy = 0.0519. a. Compute MSR and MSE (to 3 decimals). MSR MSE h Compute the F tost statistic (to 2 decimals) Use Etable
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
![The following educational exercise involves data that were designed to be solved using Excel. The estimated regression equation presented is based on 10 observations:
\( \hat{y} = 29.1270 + 0.5906x_1 + 0.4980x_2 \).
Given:
- \( SST = 6,942.625 \)
- \( SSR = 6,737.375 \)
- \( s_{b_1} = 0.0894 \)
- \( s_{b_2} = 0.0519 \)
### Tasks:
**a. Compute MSR and MSE (to 3 decimals).**
- **MSR:** [Blank]
- **MSE:** [Blank]
**b. Compute the F test statistic (to 2 decimals). Use F table.**
- **F test statistic:** [Blank]
What is the p-value?
- Options: "less than .01" (selected).
At \( \alpha = .05 \), what is your conclusion?
- **Conclusion:** The overall model is significant (selected).
**c. Compute the t test statistic for the significance of \( \beta_1 \) (to 2 decimals). Use t table.**
- **t test statistic for \( \beta_1 \):** [Blank]
The p-value is:
- Options: "less than .01" (selected).
At \( \alpha = .05 \), what is your conclusion?
- **Conclusion:** There is a significant relationship between \( y \) and \( x_1 \) (selected).
**d. Compute the t test statistic for the significance of \( \beta_2 \) (to 2 decimals).**
- **t test statistic for \( \beta_2 \):** [Blank]](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F56b29ac1-2bc2-4707-9f70-7bacc854483d%2F04f1a9aa-865a-4397-b80d-639e3fa3dcac%2Fcgdh6dl_processed.gif&w=3840&q=75)

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