Which of the following correctly describes the interpretation of an r2 statistic of 0.673 in a model relating BMI (kg/m2) (X) to frequency of hospital visits (Y)? There is a high degree of correlation between BMI and frequency of hospital visits There is a strong, positive relationship between BMI and frequency of hospital visits 67.3% of hospital visits are due to elevated levels of BMI 67.3% of the variation in frequency of hospital visits is explained by BMI
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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Which of the following correctly describes the interpretation of an r2 statistic of 0.673 in a model relating BMI (kg/m2) (X) to frequency of hospital visits (Y)?
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There is a high degree of
correlation between BMI and frequency of hospital visits -
There is a strong, positive relationship between BMI and frequency of hospital visits
-
67.3% of hospital visits are due to elevated levels of BMI
-
67.3% of the variation in frequency of hospital visits is explained by BMI
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