For the following multiple regression which was conducted to attempt to predict the price of yachts based on the independent variables shown,  Regression Statistics Multiple R 0.890579188 R Square 0.793131289 Adjusted R Square 0.7379663 Standard Error 30.28395534 Observations ? ANOVA   df SS MS F Regression ? 52743.23074 ? ? Residual 15 ? 917.1179509 Total 19 66500   Coefficients Standard Error t Stat P-value Intercept 73.33291 62.25276 1.17799 0.25715 Age -0.13882 0.05353 -2.59326 0.02037 Length 3.73984 0.95568 3.91328 0.00138 Nav Eqp 0.37644 0.16876 2.23061 0.04140 Flying Bridge 17.70752 15.57847 1.13667 0.27351 Write down the fitted multiple regression equation Use the p-value approach to test the significance of the individual regression coefficients at the 5% level of significance Find the percentage variation in the price of yachts that is explained by the regression model How many yachts were considered in this study

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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.