Please do c,d and e in detail

Big Ideas Math A Bridge To Success Algebra 1: Student Edition 2015
1st Edition
ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
Publisher:HOUGHTON MIFFLIN HARCOURT
Chapter4: Writing Linear Equations
Section: Chapter Questions
Problem 11CT
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Please do c,d and e in detail 

ONSHIPS
ew Exercises
R3.3 Stats teachers' cars A random sample of AP® Sta-
tistics teachers was asked to report the age (in years)
and mileage of their primary vehicles. A scatterplot
of the data, a least-squares regression printout, and
a residual plot are provided below.
Predictor
Сoef
SE Coef
T
P
Constant
3704
8268
0.45
0.662
Age
12188
1492
8.17
0.000
S = 20870.5
R-Sq = 83.7%
R-Sq(adj)
= 82.4%
160,000
140,000
120,000
100,000
80,000
60,000
40,000
20,000
2
4
6.
8
10
12
Age
60,000
50,000
40,000
30,000
20,000
10,000
-10,000
-20,000
-30,000
2
4
6.
8
10
12
Age
(a) Give the equation of the least-squares regression
line for these data. Identify any variables you use.
(b) One teacher reported that her 6-year-old car had
65,000 miles on it. Find and interpret its residual.
(c) What's the correlation between car age and mile-
age? Interpret this value in context.
(d) Is a linear model appropriate for these data? Ex-
plain how you know.
(e) Interpret the values of s and r².
Mileage
Residual
Transcribed Image Text:ONSHIPS ew Exercises R3.3 Stats teachers' cars A random sample of AP® Sta- tistics teachers was asked to report the age (in years) and mileage of their primary vehicles. A scatterplot of the data, a least-squares regression printout, and a residual plot are provided below. Predictor Сoef SE Coef T P Constant 3704 8268 0.45 0.662 Age 12188 1492 8.17 0.000 S = 20870.5 R-Sq = 83.7% R-Sq(adj) = 82.4% 160,000 140,000 120,000 100,000 80,000 60,000 40,000 20,000 2 4 6. 8 10 12 Age 60,000 50,000 40,000 30,000 20,000 10,000 -10,000 -20,000 -30,000 2 4 6. 8 10 12 Age (a) Give the equation of the least-squares regression line for these data. Identify any variables you use. (b) One teacher reported that her 6-year-old car had 65,000 miles on it. Find and interpret its residual. (c) What's the correlation between car age and mile- age? Interpret this value in context. (d) Is a linear model appropriate for these data? Ex- plain how you know. (e) Interpret the values of s and r². Mileage Residual
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