22. In exercise 4, the following estimated regression equation relating sales to inventory in- vestment and advertising expenditures was given. ŷ = 25 + 10x, + 8x, The data used to develop the model came from a survey of 10 stores; for these data SST = 16,000 and SSR = 12,000. a. Compute SSE, MSE, and MSR. b. Use an F test and a .05 level of significance to determine whether there is a relation- ship among the variables.
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.
In exercise 4, the following estimated regression equation relating sales to inventory investment and advertising expenditures was given.
The data used to develop the model came from a survey of 10 stores; for these data
SST = 16,000 and SSR =12,000.
yˆ = 25 + 10x1 + 8x2
a. Compute SSE, MSE, and MSR.
b. Use an F test and a .05 level of significance to determine whether there is a relationship among the variables.
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