If your answer is zero, enter "0". a. Write the estimated regression equation (to 4 decimals). b. Use a t test to determine whether monthly maintenance expense is related to usage at the 0.05 level of significance (to 2 decimals). Use Table 2 of Appendix B. t = p-value = Reject v the null hypothesis. Monthly maintenance expense is not v related to usage. c. Did the estimated regression equation provide a good fit? Explain. Hint: If r2 is greater than 0.50, the estimated regression equation provides a good fit. because the value of r2 is less v than 0.50. No
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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