A least squares regression line was calculated to relate the length (cm) of newbom boys to their weight in kg. The regression analysis gives the model Weight = -5.11+0.1952 Length. Complete parts a through c below. O D. For every additional 1 kg of weight, the length of the baby is predicted to increase by 0.1952 mm. b) If a baby is 53 cm long, what is his predicted weight? O kg (Round to two decimal places as needed.) c) Consider a baby boy that was 48 cm long and weighed 3 kg. According to the regression model, what was his residual? What does that say about him? The residual isO. (Round to two decimal places as needed.) This means that the baby is kg (Round to two decimal places as needed.) than predicted by his length.
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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