Given the following fragment of an output produced by a regression software package (with some values missing), find the value of MSE: ANOVA Significance df SS MS F F Regression 8 551.7558 ? ? 0.0000023 Residual 78 199.3113 ? Round your answer to three decimal places. Your Answer: Answer

The table below shows the profit, P(x), in dollars, from selling x items. 1 2 3 6 9 14 P(x) 66.1 82.4 88.9 49.6 -77.9 -486.4 Using your calculator to do a quadratic regression, express the profit as a function of the number of items sold. P(x) = Round all numbers to 1 decimal place. Using your quadratic regression, estimate the profit from selling 5 items? Select an answer v Round to 2 decimal places. Using your quadratic regression, estimate the number of items that need to be sold to make a profit of $-25.6 ? Select an answer

Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary=11,722.40+3182.56(Education)+1202.44(Experience)Estimated Salary=11,722.40+3182.56(Education)+1202.44(Experience)  Suppose an employee with 66 years of education has been with the company for 33 years (note that education years are the number of years after 8th8th grade). According to this model, what is his estimated annual salary?

Can I include the dummy variables in regression equation like Y=a+bX+u where the X is the vector of x variables that contain dummy variables with 5 categories? how should I write my general regression equation with this?

(2)What would the consequence be for a regression model if theerrors were not homoscedastic?

Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary=11,681.31+3418.97(Education)+1194.78(Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree (10 years of education). How much more money would we expect the employee with a master's degree to make?

2. Suppose you run a regression with quantity as your dependent variable and advertising as one of your independent variables. The p-value on advertising is .08. The marketing team is arguing that their advertising efforts are impacting sales, but the finance/economics department is arguing that there isn’t evidence that the advertising is impacting sales. What side would you take and why? Note that this question squarely hits the idea that stats is part science/part art...

A company wants to use regression analysis to forecast the demand for the next quarter.In such a regression model, demand would be the independent variable. True or false?a. Trueb. False

What are the various functional forms of Regression Model?

Explain how you will use Regression analysis in any research with a suitable example.