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?

What effect would this salary increase have on the estimated coefficient of the intercept,

Consider the following output for a linear model for estimating the salary of employees at a company (in $) by the number of years employed at the company. > technitron.lm = lm(salary ~ yrs.empl, data = technitron.df)> newdata = list(yrs.empl = c(6, 8))> predict(technitron.lm, newdata, interval = "confidence") fit lwr upr1 35037.47 32582.25 37492.692 37251.91 35024.31 39479.50> predict(technitron.lm, newdata, interval = "prediction") fit lwr upr1 35037.47 20396.88 49678.062 37251.91 22647.76 51856.05Give the appropriate interval for the average salary of employees who have been employed for 6 years.Group of answer choices(32582.25, 37492.69)(20396.88, 49678.06)(35024.31, 39479.50)(22647.76, 51856.05)

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.

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.

Starting salaries in the United States for associates with master's degrees in financial engineering (FE) have been rising approximately linearly, from $74,800 in 2009 to $89,800 in 2013.†(a)Use the two (year, salary) data points (0, 74.8) and (4, 89.8) to find the linear relationship y = mx + b between x = years since 2009 and y = salary in thousands of dollars.y = 3.75x+74.8 (b)Use your formula to predict a new FE associate's salary (in dollars) in 2038. [Hint: Since x is years after 2009, what x-value corresponds to 2038?] (Round your answer to the nearest dollar.)