The authors of the paper "Weight-Bearing Activity during Youth Is a More Important Factor for Peak Bone Mass than Calcium Intake"t used a multiple regression model to describe the relationship between y- bone mineral density (g/cm) X- body weight (kg) X -a measure of weight-bearing activity, with higher values indicating greater activity (a) The authors concluded that both body weight and weight-bearing activity were important predictors of bone mineral density and that there was no significant interaction between body weight and weight-bearing activity. What multiple regression function is consistent with this description? (Use a to represent the intercept. Use , and , for the coefficients of x, and x) (b) The value of the coefficient of body weight in the multiple regression function given in the paper is 0.569. Interpret this value. O When the measure of weight-bearing activity is fixed, and body weight is increased by 0.569-kg, the mean bone mineral density increases by 1 g/cm. O When the measure of weight-bearing activity and body weight are simultaneously increased by 1 unit each, the mean bone mineral density increases by 0.569 g/cm. O When the measure of weight-bearing activity is fixed, for a 1-kg increase in body weight, the mean bone mineral density increases by 0.569 g/cm. O When body weight is fixed, and the measure of weight-bearing activity is increased by 0.569 units, the mean bone mineral density increases by 1 g/cm. O When body weight is fixed, for a 1 unit increase measure of weight-bearing activity, the mean bone mineral density increases by 0.569 g/cm.
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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