Which of the following would you expect to be a problem associated with adding lagged regressors into a regression equation in order to “cure” autocorrelation? Select one: a. The assumption that the regressors are non-stochastic is violated. b. Adding lags may induce multicollinearity with current values of variables. c. The standard errors of the coefficients will fall as a result of adding more explanatory variables. d. A model with many lags may lead to residual non-normality.
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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