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 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:

= 1                    Weekday (Mon to Fri)

       0                    Weekend (Sat and Sun)

= 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, because it's weekday and 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.

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