a) Use software to find the multiple linear regression equation. Enter the coefficients rounded to 4 decimal places. b) Use the multiple linear regression equation to predict the salary for a baseball player with an RBI of 41 and HR of 25. Round your answer to 1 decimal place, do not convert numbers to dollars. millions of dollars c) Holding all other variables constant, what is the correct interpretation of the coefficient b1 = 0.111 in the multiple linear regression equation? %3D O For each HR, a baseball player's predicted sallary increases by 0.111 million dollars. OFor each RBI, a baseball player's predicted sallary increases by 0.111 million dollars. O f the baseball player's salary increases by 0.111 million dollars, then the predicted RBI will increase by one. O If the baseball player's salary increases by 0.111 million dollars, then the predicted RBI will increase by 0.0371. d) Holding all other variables constant, what is the correct interpretation of the coefficient b = 0.0371 in the multiple linear regression equation? O If the baseball player's salary increases by 0.0371 million dollars, then the predicted HR will increase by one. O For each HR, a baseball player's predicted sallary increases by 0.0371 million dollars. O If the baseball player's salary increases by 0.0371 million dollars, then the predicted HR will increase by 0.111. O For each RBI, a baseball player's predicted sallary increases by 0.0371 million dollars.
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.
We wish to predict the salary for baseball players (y) using the variables RBI (x1) and HR (x2), then we use a regression equation of the form yˆ=b0+b1x1+b2x2
- HR - Home runs - hits on which the batter successfully touched all four bases, without the contribution of a fielding error.
- RBI - Run batted in - number of runners who scored due to a batters's action, except when batter grounded into double play or reached on an error
- Salary is in millions of dollars.
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