UMMARY OUTPUT Regression Statistics Multiple R 0.4746 R square 0.2252 Adjusted R Square 0.2091 Standard Error 466.32 Observations 50 ANOVA df SS MS F Significance F Regression 1 3.03E+06 3.03E+06 13.95 0.0005 Residual 48 1.04E+07 2.17E+05 Total 49 135E+07 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 1,768.32 99.42 17.79 0.0000 1,568.42 1968.21 Red Sox away game (1=yes, 0=no) 496.25 132.85 3.74 0.0005 229.13 763.38 Is the relationship between Red Sox away games and average daily revenues significant at the 95% confidence level? Choose the correct answer with the corresponding correct reasoning. No, because R Square is less than 50% Yes, because the slope is positive. Yes, because the p-value of the intercept is less than 0.05 Yes, because the p-value of the intercept is less than 0.95 Yes, because the p-value of the independent variable is less than 0.05 Yes, because the p-value of the independent variable is less than 0.95
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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