Suppose that two variables, X and Y, are negatively associated. Does this mean that above-average values of X will always be associated with below-average values o Y? Explain. Choose the correct answer below. O A. No, because there will always be at least one point that does not fit the trend. O B. Yes, because if one or more above-average values of X are associated with above-average values of Y, the variables cannot be negatively associated. O C. No, because association does not mean that every point fits the trend. The negative association only means that above-average values of X are generally associated with below-average values of Y. D. No, because when two variables, X and Y, are negatively associated, above-average values of X are associated with above-average values of Y.
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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