15. For the following multiple regression which was conducted to attempt to predict the Brand Loyalty based on the independent variables shown, Regression Statistics Multiple R R Square Adjusted R Square| Standard Error 0.5627 0.3166 0.3039 0.5538 Observations 219 ANOVA Significance df SS MS F F Regression Residual Total ? ? ? 0.0000 214 65.6223 0.3066 218 96.0274 Standard Coefficients 2.3537 t Stat P-value Lower 95% Upper 95% 2.7394 0.3379 0.1667 Error 0.1957 12.0283 0.0000 1.9680 Intercept Brand Awareness 0.2201 0.0597 3.6846| 0.0003 0.1024 Brand Association 0.0700 0.0491 1.4253 0.1555 -0.0268 Perceived Value 0.0482 0.1644 0.0590 0.8173| 0.4147 0.0477 2.6975 0.0075 -0.0680 Perceived Quality 0.1286 0.0346 0.2225 a. Find the missing entries denoted by "?" in the above ANOVA table. b. Write down the fitted multiple regression equation c. Use the p-value approach to test the significance of the individual regression coefficients at the 5% level of significance d. Find the percentage variation in the Brand Loyalty that is explained by the regression model ·

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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.