A pediatrician wants to determine the relation that exists between a child's height, x, and head circumference, y. She randomly selects 11 children from her practice, measures their heights and head circumferences, and obtains the accompanying data. Complete parts (a) through (g) below. E Click the icon to view the children's data (a) Find the least-squares regression line treating height as the explanatory variable and head circumference as the response variable. 1 Data Table y=x+ (D (Round the slope to three decimal places and round the constant to one decimal place as needed.) Height (inches), x Head Circumference (inches), y (b) Interpret the slope and y-intercept, if appropriate. 28 176 24.25 17.2 First interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. 25.5 172 26.25 17.6 O A. For a head circumference of 0 inches, the height is predicted to be in. 24.5 171 (Round to three decimal places as needed.) 27.75 17.7 O B. For every inch increase in height, the head circumference increases by (Round to three decimal places as needed.) 174 176 174 in., on average. 26 25 27 26.75 26.75 O C. For a height of 0 inches, the head circumference is predicted to be (Round to three decimal places as needed.) in. 176 176 27.75 O D. For everv inch increase in head circumference. the heiaht increases bv in. on averaoe Done Print alr to select your answer(s).
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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