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please answer will give thumbs up! On Blackboard you can find a dataset named jtrain.csv in the data content folder. This data are the 1988

please answer will give thumbs up!
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On Blackboard you can find a dataset named jtrain.csv in the data content folder. This data are the 1988 data for Michigan manufacturing firms in JTRAIN. Suppose that you need to use this dataset to estimate this linear regression model: hrsemp=0+1grant+2lsales+3lemploy+e The dependent variable, hrsemp, is hours of training per employee at the firm level. The variable grant is a dummy variable equal to one if the firm received a job training grant for 1988, and zero otherwise. The variables 1sales and lemploy are transformed variables of annual sales and number of employees using natural logarithm (log(sales), log(employ)) as shown in class. 1) Write down the R code you can use to estimate this model. 2) Write down how you interpret the slope coefficient estimate for grant in this model. 3) Write down how you interpret the slope coefficient estimate for lemploy in this model. 4) Based on your estimation results, should you keep this variable, lsales, in your model? Why? Type here to search source Console: Termanal x (Barkground Jobs x. Type here to search G R4.2.1 : Type here to search On Blackboard you can find a dataset named jtrain.csv in the data content folder. This data are the 1988 data for Michigan manufacturing firms in JTRAIN. Suppose that you need to use this dataset to estimate this linear regression model: hrsemp=0+1grant+2lsales+3lemploy+e The dependent variable, hrsemp, is hours of training per employee at the firm level. The variable grant is a dummy variable equal to one if the firm received a job training grant for 1988, and zero otherwise. The variables 1sales and lemploy are transformed variables of annual sales and number of employees using natural logarithm (log(sales), log(employ)) as shown in class. 1) Write down the R code you can use to estimate this model. 2) Write down how you interpret the slope coefficient estimate for grant in this model. 3) Write down how you interpret the slope coefficient estimate for lemploy in this model. 4) Based on your estimation results, should you keep this variable, lsales, in your model? Why? Type here to search source Console: Termanal x (Barkground Jobs x. Type here to search G R4.2.1 : Type here to search

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