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Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? 0.844 Calculate the coefficient of determination (Round to three decimal places as needed.) What does this tell you about the explained variation of the data about the regression line? % of the variation can be explained by the regression line (Round to one decimal place as needed.) About the unexplained variation? % of the variation is unexplained and is due to other factors or to sampling error (Round to one decimal place as needed.)

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Introductory Statistics
OER Edition, 2013
Openstax
ISBN: 9781938168208

Related questions

The table shows the number of goals allowed and the total points earned​ (2 points for a​ win, and 1 point for an overtime or shootout​ loss) by
ice hockey teams over the course of a season. The equation of the regression line is
x.
Use the data to answer the following questions.
​(a) Find the coefficient of​ determination,
​,
and interpret the result.
​(b) Find the standard error of the​ estimate,
​,
and interpret the result.
Goals​ Allowed, x
​Points, y
​(a)
nothing
​(Round to three decimal places as​ needed.)

Opeele Kyinkafa sells different used 2005 GM cars in excellent condition. The value or the retail price (Price) of a car is dependent on a variety of characteristics such as number of miles the car has been driven (Mileage), manufacturer of the car (Make) such as Buick, Cadillac, Chevrolet, Pontiac, SAAB, and Saturn. The car price is also influenced by the body type (Type) such as sedan, convertible, coupe, hatchback and wagon. It is also affected by number of cylinders (Cylinders) in the engine, the engine size (Liter), cruise control which is an indicator variable representing whether the car has cruise control (yes) or no otherwise and Sound indicator representing whether the car has upgraded speakers (yes) or no otherwise. All cars in this data set were less than one year old when priced and considered to be in excellent condition. Determine which major variables are dummies and are dynamic? Identify 3 potential unobserved heterogenous factors in this dataset. Display the full descriptive statistics of the data in R. Why do you think some variables are starred (*)? What is the median for “price”, standard deviation for “mileage”, skewness for “cylinder” and mean for “sound”? Test if “price” is normally distributed using histogram, kernel density plot and the shapiro wilk test. Create a red scatterplot matrix of price, mileage, cylinder, liter, make. From your graph, is the correlation between price & mileage positive or negative? What’s the pearson correlation coefficient between price & mileage and between “cylinder” & “liter” correct to 2 d.p Create a correlation matrix of the dataset by finding the apt R command for converting all string/dummy variables From the matrix, identify 2 potentially good predictors? Identify 3 pairs of variables that are mostly multicollinear. Which 2 pairs of variables are least correlated? Identify 3 pairs of variables most highly correlated with Cylinder Generate a simple regression plot of price on mileage with a re fitted line. Run the whole multiple regression model (label the equation as "regprice") & use it to answer the other questions. Specify the regression model for the whole data keeping the exact names of the variables. Write the estimated regression equation. In one sentence, which variables are significant and which are not? Justify Is the regression model justifiable? Explain Interpret the coefficient of Mileage, MakeCadillac, TypeSedan, Cylinder, & Cruiseyes. Compare the price of a car with 130,000 mileage, 6 cylinders, 3.8 liters, with cruise and sound, was manufactured by Pontiac with a convertible body type with that of the price of a car with four cylinders, 120,000 mileage, 3.8 liters, without cruise nor sound, was manufactured by Cadillac with a hatchback body type. Which factor(s) appears to be causing a comparative difference (if any)? Using only the VIF, which one of the pairs of variables selected to be multicollinear may be deleted? Justify?

Since Thorndike “Graph-Pro” racquetball racquets were introduced several years ago, no attempt has ever been made to offer a lightweight version. Ted has done some research and found that some of the other manufacturers offer a lighter version of their standard racquet. In addition, some of the racquetball players he has talked to have said a lighter racquet would probably improve their game.

Talking with production engineers, Ted learns that the racquets coming off the line don’t all weigh the same anyway. According to the chief engineer, the racquets weigh an av- erage of 240 grams, but the weights “vary all over the lot,” and he takes advantage of the situation to press for a high-tech $700,000 machine that would produce racquets of equal quality while holding this variation within narrower limits.

Old Luke isn’t too keen on buying a $700,000 machine, especially since Ted might have a better solution. Ted has dusted off the literature that accompanied the racquet-production machine and found that the machine generates output that is approximately normally distributed, with a standard deviation of 10 grams. This is a little sloppy these days, but maybe Thorndike Sports Equipment can turn this weakness into a strength.

Conversing further with Luke, talking to three sporting goods retailers, and interviewing players at five different racquetball facilities, Ted comes back to the office with a terrific idea. Asking Luke to sit down, and bringing him some coffee, Ted begins his pitch: “Say, grandfather, why don’t we take the racquets at the lighter end of the range and label them ‘Graph-Pro Light,’ with the ones more in the middle being ‘Graph-Pro Regular,’ and the ones at the heavier end can be ‘Graph-Pro Stout’?”

Luke responds that just because this works for the beer companies, this doesn’t mean it will work for Thorndike Sports Equipment. However, he’s willing to give it a try. Af- ter accompanying Ted on another round of conversations with retailers and players, the elder Thorndike tells Ted that for now, he’d like to see 15% of the production consist of “Graph-Pro Light,” with 80% “Graph-Pro Regular,” and 5% “Graph-Pro Stout.”

Ted’s next task is to tell the production people how to go about selecting which racquets are to be put into these three different categories.

(a) What is the weight below which racquets classify as Graph-Pro Light? (b) What is the weight above which racquets classify as Graph-Pro Stout?

 

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