Analyze at least two of the X variable’s correlation level with Y variable.  Explain the correlation based upon the p test. Use the summary output for the data, which is found below: SUMMARY OUTPUT                                   Regression Statistics               Multiple R 0.807187704               R Square 0.651551989               Adjusted R Square 0.644440805               Standard Error 143.9428959               Observations 51                                 ANOVA                   df SS MS F Significance F       Regression 1 1898399.614 1898399.614 91.62356067 8.42534E-13       Residual 49 1015258.307 20719.55729           Total 50 2913657.922                                 Coefficients Standard Error

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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.