A pediatrician wants to determine the relation that exists between a child's height, x, and head circumference, y She randomly selects 11 children trom her präcliče, measures thei helghts and nead urCumiurences, aAa accompanying data. Complete parts (a) through (g) below. EA Click the icon to view the children's data Interpret the y-intercept, if appropriate. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. O Data Table O A. For every inch increase in head circumference, the height increases by in, on average. (Round to one decimal place as needed.) Height (inches), x Head Circumference (inches), y E O B. For a height of 0 inches, the head circumference is predicted to be in (Round to one decimal place as needed.) 27.75 17.7 24 25 17.2 172 OC. For every inch increase in height, the head circumference increases by in on average. (Round to one decimal place as needed.) 25.5 25 75 24.5 17.6 17.1 OD. For a head circumference of 0 Inches, the height is predicted to be (Round to one decimal place as needed.) in 28 17.8 26.5 175 OE. It is not appropriate to interpret the y-intercept 17.7 27.25 26.75 17.5 17.6 (c) Use the regression equation to predict the head circumference of a child who is 24 5 inches tall 26 75 27 75 177 -in (Round to two decimal places as needed) Print Done t0 select VOur answeris)

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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.