In this report, we are interested in determining if there is any relationship between the dependent variable (y) business friendliness and the independent variables: change in revenue, state economy, black, Hispanic, and Asian. In this case we are interested with a multiple linear relationships between the dependent variable and independent variable.
Problem statement
In this study, the main idea behind this work is to determine if there is any relationship between the regressor variable business friendliness and the predictor variables; Asian, Hispanic, Black, State Economy, and Change in revenue. These predictor variables may directly contribute to the dependent variable business friendliness. In this study, we will also be interested in determining if the multiple regression model account for how much of the errors in the model.
Hypothesis
H0; there is no significant relationship between the business friendliness and Asian
Ha; there is a significant relationship between the business friendliness and Asian
H0; there is no significant relationship between the business friendliness and Hispanic
Ha; there is a significant relationship between the business friendliness and Hispanic
H0; there is no significant relationship between the business friendliness and Black
Ha; there is a significant relationship between the business friendliness and Black
H0; there is no significant relationship between the business friendliness and State of the economy
Ha; there is a significant relationship between the business friendliness and state of the economy
The regression analysis
Finding and conclusion
business =42.03+1.27 Asian+4.18 Black+18.25 State of economy+6.94 Change revenue
This implies that, a change of one unit of state of economy lead to a change of business friendliness by 18.25 units, a change of one unit of revenue lead to an increase of the business friendliness by 6.94, a change of one unit in Asian lead to an increase of 1.27 units in business friendliness, a change of one unit of Black lead to an increase of 4.18 units of business friendliness.
The multiple regression models when the independent variable chief executive is added.
Finding and conclusion
When the chief executive variable was added the following was observed. The t-value of the chief executive was -9.26051 with a p-value of 0.0000 which is less that the o.05 level of confidence. This implies that the chief executive is significant to the regression model. The coefficient of determination rises to 0.1408, which implies that the new model can account for 14.08% of the errors in the model.
The new multiple regression
The normal probability plot
