A national homebuilder builds​ single-family homes and​ condominium-style townhouses. The accompanying dataset provides information on the selling​ price, lot​ cost, and type of home for closings during one month.   Develop a multiple regression model for sales price as a function of lot cost and type of home.   Create a dummy variable named​ "Townhouse", where it is equal to 1 when Type=​"Townhouse" and 0 otherwise. Determine the coefficients of the regression equation.   Type Sales_Price Lot_Cost Townhouse 112740 20700 Single Family 136530 25500 Townhouse 147905 24650 Single Family 170000 25200 Townhouse 181916 45025 Townhouse 187390 27000 Single Family 189120 35000 Townhouse 196898 45025 Townhouse 203076 45025 Single Family 205821 39299 Single Family 214205 36500 Townhouse 250800 73400 Single Family 255000 43198 Single Family 268000 43344 Single Family 268500 41099 Single Family 271105 45000 Single Family 277720 44650 Single Family 294990 57000 Single Family 301500 59000 Single Family 307387 45850 Single Family 312898 40768 Single Family 319602 82250 Single Family 324412 62523 Single Family 337374 70399 Single Family 337380 49150 Single Family 338065 54850 Single Family 354117 56219 Single Family 359949 50591 Single Family 432426 57422 Single Family 492820 84122   Sales Price=_________+​________•Lot Cost+​___________•Townhouse ​(Round the constant and coefficient of Townhouse to the nearest integer as needed. Round all other values to two decimal places as ​needed.)

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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.