If variables have a linear relationship then which of these could be true:
A)There could be a cause and effect relationship between the two variables
B)There could be no cause/effect, just a statistical relationship between the two variables
C)When the valuable of one variable goes up, the value of the other variable goes up
D)When the one variable of variable goes down, the value of the other goes down
E)All of the above
We want to test the effect that GPA might have on grades in a class. What is the dependent variable
A)GPA
B)The grades
C)Regression
D)Coefficient
We want to test whether GPA has a linear effect on grades in the class.Which of these is an appropriate statistical analytical model?
A)Multiple regression
B)Simple Linear Regression
C)Double moving average
D)Exponential Smoothing
The coefficient of determination in a regression model:
A)Tells us the percentage of variability in the dependent variable accounted for by the independent variable
B)Is represented by R-squared
C)Is always some value between 0 and 1
D)All of the above
Suppose we analyzed the effect of GPA on grades in a class and found the results to have an R-squared value of 0.53.What do we know?
a)Fifty-three percent of the variability in class grades is attributable to GPA
b)There are other factors (besides GPT) that account for 47% of grades in the class
c)Neither A or B
d)Both A and B
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Use this data in Excel to run multiple regression analyses. Follow the information in the text and experiment with this data. NOTE: BR is bedrooms. The reason for some having a "half" bedroom is that the data is coded in a way that a den was counted as .5 of a bedroom. So 2.5 means 2 bedrooms plus a den. DO NOT INCLUDE PRSQFT as an independent variable. That is there for comparison purposes. The homework for this week has two parts. First, "think out loud" on the discussion board. As you examine this data, read the text, and experiment with the regression, post your findings as you go. You don't have to post everything, but just a few tips. Work together with the rest of the class. Read the posts to see how the others are approaching this data set. I will also provide some guidance along the way on the discussion board. Unlike normal weeks where 1 post is required, this week a minimum of 3 substantive posts is required, not just one post and two replies.. Feel free to add more. These don't have to be long. DO NOT POST YOUR SPREADSHEET TO THE DISCUSSION FORUM. The second part of the homework is to, once again, analyze a potential home sale. You are looking at a home in Berkshire Lakes subdivision. The asking price is $275,000. It is 1309 square feet with 2.5 bedrooms and 2 bathrooms. It has a pool and was built in 1991. This time, you are a consulting analyst who has been asked by a realtor to analyze the home price for this home. You will do the spreadsheet work and prepare a memo for the client. Drop both the memo and the spreadsheet in the dropbox. What is this home worth? What price might it bring? Based on what evidence? Run multiple regressions in Excel to estimate the value of the home. What is your best model? Given your best model, what is the home price? Remember that you have previously analyzed this same home. Do not ignore that information. Turn in your spreadsheet along with a memo to your client with analyses and a description of what you...