Which of the following statements concerning the linear correlation coefficient are always true? I: The value of the linear correlation coefficient always lies between−1 and 1. II: If the linear correlation coefficient for two variables is zero, then there is a strong linear relationship between the variables. III: If the slope of the regression line is negative, then the linear correlation coefficient could be either negative or positive. IV: A linear correlation coefficient of −0.82 suggests a stronger linear relationship than a linear correlation coefficient of 0.62.
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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