Using the output below, predict the amount of monthly sales if monthly advertising expenses is $1,173. SUMMARY OUTPUT Regression Statistics Multiple R 0.9880 R Square 0.9762 Adjusted R Square 0.9738 Standard Error 868.4866 Observations 12 Coefficients Standard Error P-Value Intercept 759.57 2.991435587 2217390932 Monthly Advertising Expenses 1.91 0.482113498 0000000019 O $890,978 $3,000 O.-$3,000 -$890,978

• where not met in 200 iterations Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant linear correlation between advertising cost and profit. Use a significance level of 0.01 and round all values to 4 decimal places. Advertising Cost Profit 26 23 20 30 30 27 29 3 4 5 6 7 r= 8 9 10 11 Ho: p = 0 Ha: p = 0 Find the Linear Correlation Coefficient Find the p-value p-value = 29 31 The p-value is Greater than a O Less than (or equal to) a The p-value leads to a decision to Accept Ho O Do Not Reject Ho O Reject Ho The conclusion is O There is a significant negative linear correlation between advertising expense and profit. There is a significant linear correlation between advertising expense and profit. There is a significant positive linear correlation between advertising expense and profit. There is insufficient evidence to make a conclusion about the linear correlation…

The personnel director of a large hospital is interested in determining the relationship (if any) between an employee’s age and the number of sick days the employee takes per year. The director randomly selects ten employees and records their age and the number of sick days which they took in the previous year.  Employee 1 2 3 4 5 6 7 8 9 10 Age 30 50 40 55 30 28 60 25 30 45 Sick Days 7 4 3 2 9 10 0 8 5 2 Copy Data The estimated regression line and the standard error are given.  Sick Days=14.310162−0.2369(Age)   se=1.682207se=1.682207  Find the 95% confidence interval for the average number of sick days an employee will take per year, given the employee is 26. Round your answer to two decimal places.

A. run a simple regression- dependent variable is Weeks, independent variable is Age.    B. run a multiple regression with dependent variable weeks and independent variable-age, married, head, manager and sales. C. Create the regular and standardized residual plots for both.  Please show the tables when entering values of the regression for both the outputs and the scatter plots.