A regression model is fitted to data with 5 independent variables (X1, X. X, X. and X;) and the output of the analysis using SPSS is given below: Model Regression Sum of Squares df p-value 0.0000 A B Eror 17634.813 Total 38401.757 46 Coefficients Unstandardized Coefficients Std. Error 114.522 Мodel p-value B Constant) -213.5781 0.069 0.297 3.296 0.8690 0.005 0.0579 0.986 0.8010 0.120 0.000 0.0558 0.094 0.557 0.0975 0.122 0.428 Based on the output above, answer the following. (a) Find the values of A, B and C in the ANOVA table. (b) Find the coefficient of determination, Rº. (c) Interpret the R° value in part (b). (d) Find the standard error of estimate, s. (e) Find the F-test statistic value. (1) Interpret the p-value in the ANOVA table at a = 0.05. Interpret the p-value for each independent variable (X1, X2, X3, X, and X;) in the Coefficients table at a = 0.05.
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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