David's Landscaping has collected data on home values (in thousands of $) and expenditures (in thousands of $) on landscaping with the hope of developing a predictive model to help marketing to potential new clients. Data for 14 households may be found in the file Landscape. Click on the datafile logo to reference the data. (NEED ANSWERS FOR C, D, and E) c. Use the least squares method to develop the estimated regression equation (to 5 decimals). d. For every additional $1000 in home value, estimate how much additional will be spent on landscaping (to 2 decimals). e. Use the equation estimated in part (c) to predict the landscaping expenditures for a home valued at $575,000 (to the nearest whole number).
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.
David's Landscaping has collected data on home values (in thousands of $) and expenditures (in thousands of $) on landscaping with the hope of developing a predictive model to help marketing to potential new clients. Data for 14 households may be found in the file Landscape. Click on the datafile logo to reference the data.
(NEED ANSWERS FOR C, D, and E)
c. Use the least squares method to develop the estimated regression equation (to 5 decimals).
d. For every additional $1000 in home value, estimate how much additional will be spent on landscaping (to 2 decimals).
e. Use the equation estimated in part (c) to predict the landscaping expenditures for a home valued at $575,000 (to the nearest whole number).
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