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trapecia [35]
3 years ago
11

In which of the following situations can multiple regression be performed? Select all that apply. Select all that apply: predict

ing the current salary of an employee, given the initial salary and the number of years the employee has been in his or her current position predicting the number of home runs a baseball player will hit in the next season, given the number of home runs the player hit in the previous season and the number of doubles the player hit in the previous season predicting the number of sodas sold at a concert, given the attendance at a game predicting the number of cans of chicken noodle soup sold at a supermarket, given the number of flu cases in the past month
Business
1 answer:
Dimas [21]3 years ago
6 0

Answer:

a. predicting the current salary of an employee, given the initial salary and the number of years the employee has been in his or her current position

b. predicting the number of home runs a baseball player will hit in the next season, given the number of home runs the player hit in the previous season and the number of doubles the player hit in the previous season

Explanation:

Multiple regression is a regression method that is employed to to predict the value of a variable, called the dependent variable, based on the value of two or more other variables, called the independent variables.

From the question, on the following two options have one dependent and at least two independent variables as indicated below:

a. "<em>the current salary of an employee</em>" is the dependent variable. "<em>the initial salary</em>" is the first independent variable, and "<em>the number of years the employee has been in his or her current position</em>" is the second independent variable.

b. "<em>the number of home runs a baseball player will hit in the next season</em>" is the dependent variable. "<em>the number of home runs the player hit in the previous season</em>" is the first independent variable, and "t<em>he number of doubles the player hit in the previous season</em>" is the second independent variable.

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