Question

The manager of a furniture factory that operates a morning and evening shift seven days a week wants to forecast the number of chairs its factory workers will produce on a given day and shift. The production manager gathers chair production data from the factory and lists whether the production day was a weekday or a weekend (i.e., Saturday or Sunday), and whether the shift was in the morning or evening. Create a regression model to analyze the relationship between the number of chairs produced, whether a day was a weekday or weekend, and whether the shift was in the morning or evening. Be sure to include the residuals and residual plots in your analysis.

Answer 1

Answer:

Answer will be 477

Explanation:

From the details, note that the manager of a furniture factory that operates a morning and evening shifts seven days a week wants to forecast the number of chairs to be produced on a given day and shift by its factory employees.

Consider Y is the vector reflecting the number of chairs the factory produces for its employees.

The independent variables are:

$x_{1i}$ = 1                    Weekday (Mon to Fri)

       0                    Weekend (Sat and Sun)

$x_{2i}$ = 1                    Morning Shift

       0                    Evening shift.  

Observe that the regression line is as follows from the regression output given in the problem:

Ŷ = 405.58 + 70.97 * Weekday + 47.85 * Shift.  

Calculate the number of chairs during the evening shift which will be generated on a Thursday.

For this problem, $x_{1} = 1$ because it's weekday and $x_{2} = 0$ because it's a shift from the evening.

Ŷ = 405.58 + 70.97 * Weekday + 47.85 * Shift.  

  = 405.58 + 70.97 * (1) + 47.85 * (0)

  = 405.58 + 70.97 + 0

  = 476.55  

  = 477

Thus, the number of chairs that will be generated during the evening shift on Thursday will be 477.

Answer 2

Answer:

Detailed solution is given below: