The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicte weight of a bear with a chest size of 44 inches. Is the result close to the actual weight of 303 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 45 265 Click the icon to view the critical values of the Pearson correlation coefficient r. 50 321 41 52 45 45 221 335 307 265 What is the regression equation? y =+ x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 44 inches? The best predicted weight for a bear with a chest size of 44 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 303 pounds? O A. This result is close to the actual weight of the bear. O B. This result is exactly the same as the actual weight of the bear.
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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