Prove this statement "Regression models used for forecasting need not have a causal interpretation".?
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.
Prove this statement "Regression models used for forecasting need not have a causal interpretation".?
Regression Analysis is a statically technique which is used to find a linear relationship between two variables , one is dependent that we are trying to estimate with the help of an independent variable .In predictive analysis main concern is to find the linear relationship between dependent and independent variable and then use this relationship to predict the value of dependent variable for the given value of independent variable .In predictive analysis , dependent and independent are linearly related but it can not be said that change in y is due to change in x i.e. x causes any change in Y.
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