A realty group would like to develop a regression model to help it set weekly rental rates (y) for beach properties during the summer season. The independent variables for this model are the number of bedrooms a property has (x,), its age in years (x2), and the number of blocks away from the ocean the property is (x3). Use the data provided to complete parts a through e below. E Click the icon to view the data for randomly selected rental properties. a) Construct a regression model using all three independent variables. ŷ = (D + (O×, + (O*2 + (Dx3 (Round the constant term to the nearest integer. Round the coefficients of x,, X2, and x3 to one decimal place as needed.)
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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