For the Salaries data set, create scatter diagrams showing the relationship between each possible explanatory variable and salaries. Are there any obvious problems? Are there some variables that seem particularly strong as candidates for explanatory variables?
Answer to relevant QuestionsCheck the Excel output for the models created in Exercises 6, 7, and 8 above for outliers. If you had access to the original records for this data set, what would you do? Compare the adjusted R2 values for the three models of salary from Exercises 12, 13, and 14 above. Based on the adjusted R2, which model does not seem worth considering at this point? Does the Woodbon model that includes mortgage rates and advertising expenditure meet the required conditions for regression? If so, conduct an F-test on the significance of the model. A production manager has collected data on the number of units produced and the number of employees at work, for the day shift and the night shift. Is shift a significant explanatory variable for the number of units ...The multiple regression model for monthly credit card balances and the age of the head of household, income (in thousands of dollars), and the value of the home (in thousands of dollars) is described in the Excel output ...
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