which of the following are advantages of principal component regression select all that are true and also explain the answers in some lines. 1 it is robust against non normality 2 interpretations of regression coefficients is simpler compared to using the original predictors. 3 we can use fewer terms in our model without much loss of information from our predictors. 4 we retain infromation from all predictor variables,. 5 there will be no multicollineairty.
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.
which of the following are advantages of principal component regression
select all that are true and also explain the answers in some lines.
1 it is robust against non normality
2 interpretations of regression coefficients is simpler compared to using the original predictors.
3 we can use fewer terms in our model without much loss of information from our predictors.
4 we retain infromation from all predictor variables,.
5 there will be no multicollineairty.
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