4. Would it be reasonable to use the least-squares regression line to predict the final grade for a studentwho has missed 15 classes? Why or why not? absences<-c(0,1,2,3,4,5,6,7,8,9)grade<-c(89.2,86.4,83.5,81.1,78.2,73.9,64.3,71.8,65.5,66.2)xyplot(absences-grade,xlab="Absences",ylab="Final Grade",type=c("p","r"))Final Grade8206570750Absences80cor(absences,grade)## [1] -0.947395pricemodel<-lm(grade~absences)msummary(pricemodel)8590##Estimate Std. Error t value Pr(>|t|)## (Intercept) 88.73271.8028 49.219 3.21e-11 ***## absences -2.8273 0.3377 -8.372 3.14e-05 ***#### Residual standard error: 3.067 on 8 degrees of freedom## Multiple R-squared: 0.8976, Adjusted R-squared: 0.8848## F-statistic: 70.09 on 1 and 8 DF, p-value: 3.143e-05

Solution: The independent variable or explanatory variable is Absences The response or dependent…

Answered: Would it be reasonable to use the…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Explain what are the least-squares line and Regression?
You are analyzing a dataset with 932 datapoints. You decide to create a linear regression model with this dataset, using 18 predictor variables. Using this information, what is the degrees of freedom associated with the sum of squares total (total sum of squares) of your analysis?
For major league baseball teams, do higher player payrolls mean more gate money? Here are data for each of the American League teams in the year 2002. The variable x denotes the player payroll (in millions of dollars) for the year 2002, and the variable y denotes the mean attendance (in thousands of fans) for the 81 home games that year. The data are plotted in the scatter plot below, as is the least-squares regression line. The equation for this line is y = 11.43 + 0.23x. Player payroll, x (in Mean attendance, y (in $1,000,000s) thousands) Anaheim 62.8 28.52 Baltimore 56.5 33.09 40- Boston 110.2 32.72 35 Chicago White Sox 54.5 20.74 30- Cleveland 74.9 32.35 25- Detroit 54.4 18.52 Kansas City 49.4 16.30 15- Minnesota 41.3 23.70 10+ New York Yankees 133.4 42.84 Oakland 41.9 26.79 20 40 60 80 100 120 140 Seattle 86.1 43.70 Player payroll, Тarmpa Bay 34.7 13.21 X (in $1,000,000s) Техas 106.9 29.01 Toronto 66.8 20.25 Send data to calculator Send data to Excel Based on the sample data and…
A recent study showed that the hours a person exercised in a week affected the individual'sresting heart rate. It was computed that r = -.68 and the least squares regression line was?̂ = 83-1.4x, where x is the hours exercised and y is the resting heart rate. d. What percentage of variability in resting heart rate can be explained by variability inhours exercised?
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You are studying how a penguin's bill length (in mm) explains its body mass (in grams) using linear regression. You choose a non-directional alternative to be safe. Given the information below, choose the formula for the least squares regression line. b₁ = 87.42 bo = 362.31 x = 43.92 y = 4202.0 O Bill Length = 87.42 Body mass + 362.31 O Bill Length = 87.42*4202.0 + 362.31 O 4202.0 = 362.31*43.92 +87.42 O Body mass = 87.42 * Bill Length + 362.31 O Body mass = 362.31 *Bill Length + 87.42 O Body mass = 362.31 43.92 + 87.42

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Would it be reasonable to use the least-squares regression line to predict the final grade for a student who has missed 15 classes? Why or why not?