In testing multiple exclusion restrictions in the multiple regression model under the Classical assumptions, we are more likely to reject the null that some coeffcients are zero if: Select one: a. The Residuals sum of squares of the restricted model is large relative to that of the unrestricted model b. The intercept parameter is greater than the signi.cance level c. The total sum of squares, SST, is large d. The Residuals sum of squares of the restricted model is small relative to that of the unrestricted model e. Both The Residuals sum of squares of the restricted model is large relative to that of the unrestricted model and The intercept parameter is greater than the signi.cance level.
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.
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