Which of the following is true or the most appropriate explanation about regression analysis? Notice that the variable I am interested in predicting is designated as my independent variable, and the variable that I am using to predict become my predictor or dependent variable. The purpose of regression analysis is to make predictions about the value of the dependent variable given certain values of the predictor variable. O Stronger correlations lead to less accurate predictions. The simple linear regression is really a more powerful tool than simple correlation analysis
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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