Fill in the blanks. a. In the method for polynomial regression, increasing powers of the predictor variable are added until the t-test for the utility of the highest-degree term is not significant. b. In the method of polynomial regression, if the t-test for the utility of the highest-degree term is not significant, then that term is removed from the regression equation. c. In the second-order polynomial regression equation involving predictor variables x1 and x2, the cross-product term is given by . d. In a term involving a product of powers of predictor variables, the sum of the powers is called the of the term.
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.
Fill in the blanks.
a. In the method for polynomial regression, increasing powers of the predictor variable are added until the t-test for the utility of the highest-degree term is not significant.
b. In the method of polynomial regression, if the t-test for the utility of the highest-degree term is not significant, then that term is removed from the regression equation.
c. In the second-order polynomial regression equation involving predictor variables x1 and x2, the cross-product term is given by .
d. In a term involving a product of powers of predictor variables, the sum of the powers is called the of the term.
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