The data show the list and selling prices for several expensive homes. Find the regression equation, letting the the list price be the independent (x) va selling price of a home having a list price of $2 million. Is the result close to the actual selling price of $1.5 million? Use a significance level of 0.05. List price (millions of $) Selling price (millions of $) 3.4 3.6 3.4 3.7 2.8 2.4 2.1 2.1 2.6 2.8 2.6 1.6 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y =+x (Round to four decimal places as needed.) What is the best predicted selling price of a home having a list price of $2 million? The best predicted selling price for a home having a list price of $2 million is $million. (Round to two decimal place as needed.) Is the result close to the actual selling price of $1.5 million? O A. The result is close to the actual selling price of $1.5 million. O B. The result is exactly the same as the actual selling price of $1.5 million. O C. The result is not close to the actual selling price of $1.5 million.
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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