Question 2: The estimated regression equation for a model involving two independent variables and 65 observations is: yhat = 55.17+1.1X1 -0.153X2 Other statistics produced for analysis include: SSR = 12370.8, SST = 35963.0, Sb1 = 0.33, Sb2 = 0.20.a. Interpret b1 and b2 in this estimated regression equation b. Predict y when X1 = 65 and X2 = 70. c. Compute R-square and Adjusted R-Square. d. Comment on the goodness of fit of the model. e. Compute MSR and MSE. f. Compute F and use it to test whether the overall model is significant using a p-value (α = 0.05). g. Perform a t test using the critical value approach for the significance of β1.Use a level of significance of 0.05. h. Perform a t test using the critical value approach for the significance of β2.Use a level of significance of 0.05.
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.
Question 2:
The estimated regression equation for a model involving two independent variables and 65 observations is:
yhat = 55.17+1.1X1 -0.153X2
Other statistics produced for analysis include: SSR = 12370.8, SST = 35963.0, Sb1 = 0.33, Sb2 = 0.20.
a. Interpret b1 and b2 in this estimated regression equation
b. Predict y when X1 = 65 and X2 = 70.
c. Compute R-square and Adjusted R-Square.
d. Comment on the goodness of fit of the model.
e. Compute MSR and MSE.
f. Compute F and use it to test whether the overall model is significant using a p-value (α = 0.05).
g. Perform a t test using the critical value approach for the significance of β1.
Use a level of significance of 0.05.
h. Perform a t test using the critical value approach for the significance of β2.
Use a level of significance of 0.05.
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