A school district wants to understand the relationship between SOL testing, teacher salary, and teacher tenure. They fit a multiple linear regression model, with the output shown below.Use this output to answer the following TWO questions. Flag question: Question 18Question 18Tips8.5 ptsWhat is the slope for teacher tenure? Round to four decimal places.

A mathematics teacher wanted to see the correlation between test scores and homework. The homework grade (x) and test grade (y) are given in the accompanying table. Write the linear regression equation that represents this set of data, rounding all coefficients to the nearest tenth. Using this equation, find the projected test grade, to the nearest integer, for a student with a homework grade of 72.Homework Grade (x) Test Grade (y)6565 52527878 82827171 70707676 73738484 84845656 45456868 60607272 57577878 7777Copy Values for CalculatorOpen Statistics CalculatorAnswerAttempt 1 out of 2Regression Equation: Final Answer:

Suppose you are the owner of a dairy company that produces milk powder. There is a fixed cost 6.4 thousand dollars every month and variable cost 9.41 thousand dollars per ton of milk powder. Write down the monthly total cost function (dollars in thousands) in the quantity of production Q (in tonnes). What is the slope of this linear function? Question 2 Answer a. none of the others b. -0.68 c. 6.4 d. 8.10 e. 9.41

Using a sample of recent university graduates, you estimate a simple linear regression using the initial annual salary as the dependent variable and the graduate's weighted average mark (WAM) as the explanatory variable. If the regression model has an estimated intercept of 3200 and an estimated slope coefficient of 550, what is the predicted starting salary of a student with a WAM of 67?

A consumer's spending is widely believed to be a function of their income. To estimate this relationship, a university professor randomly selected 19 of his students and collected information on their spending (Y, in dollars) and income (X, in dollars) patterns in week 6 of the semester. Assuming a linear relationship between Y and X, the professor used the least-squares method and found that the Y intercept = 20.90 and the slope = 0.66. Based on this information, the slope should be interpreted as: a. For each increase of $1 in a student's weekly income, his/her mean value of weekly spending is estimated to increase by $0.66 (or 66 cents). b. For each increase of $1in a student's weekly spending, his/her mean value of weekly income is estimated to increase by $0.66 (or 66 cents). c. For each increase of $1 in a student's daily income, his/her mean value of daily spending is estimated to increase by 0.66 cents. d. For each increase of $1in a student's weekly income, his/her mean value of weekly spending is estimated to increase by $20.90.

Using the multiple linear regression output above, what is the slope for wins?Round to three decimal places.