Refer to the Minitab display below, which is based on a sample of 54 bears. The regression equation is WEIGHT = -277 - 0.89 HEADLEN + 0.46 LENGTH+ 11.8 CHEST Predictor Constant HEADLEN LENGTH CHEST Coef - 277 - 0.89 SE Coef - 8.03 - 0.16 34.49 5.672 1.107 0.000 0.876 0.46 11.8 0.42 0.660 1.121 10.53 0.000 A bear is found to have a head length of 18.0 inches, a length of 78.0 inches, and a chest size of 47.0 inches. a. Find the predicted weight of the bear. The predicted weight is (Round to the nearest whole number as needed.)
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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