MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Transcribed Image Text:Part a. Use the area below to draw a scatter diagram.
Part c.
1000
800
600
400
e.
200
We
ANOVA
Back
0
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
Regression
Residual
Total
Intercept
0
10
R-Sq=
R-Sq (adj) =
20
Chart Title
df
0.87730836
0.76966997
30
40
Weight (oz)
0.75431463
94.9755379
17
can conclude
cannot conclude
●Series1
The regression equation is (to 1 decimal)
Price(pred) =
+
b. Does there appear to be any relationship between these two variables?
There appears to be a
(to 4 decimals)
(to 4 decimals)
(to 4 decimals)
●
15
16 587440.9412
Automobile racing, high-performance driving schools, and driver education programs run by automobile clubs continue to grow in popularity. All these activities require the
participant to wear a helmet that is certified by the Snell Memorial Foundation, a not-for-profit organization dedicated to research, education, testing, and development of helmet
safety standards. Snell "SA" (Sports Application)-rated professional helmets are designed for auto racing and provide extreme impact resistance and high fire protection. One of
the key factors in selecting a helmet is weight, since lower weight helmets tend to place less stress on the neck. The data in the Excel Online file below show the weight and price
for 18 SA helmets. Construct a spreadsheet to answer the following questions.
●
50
Weight
SS
MS
Significance F
1 452135.6492 452135.6 50.1239429 3.74774E-06
135305.292 9020.353
c. Develop the estimated regression equation that can be used to predict the price given the weight. Also report the standard error of the estimate,
R-sq, and
R-sq adj.
d. Test for the significance of the relationship at the .05 level of significance.
P-value is
(to 4 decimals).
that the two variables are related.
e. Did the estimated regression equation provide a good fit?
R-sq is
(to 4 decimals).
The estimated regression equation provided a
Coefficients Standard Errort Stat P-value Lower 95% Upper 95% Lower 95% Upper 95%
2063.64585 238.7896118 8.642109 3.29E-07 1554.677839 2572.61385 1554.677839 2572.61385
4.056718472 -7.079826 3.7477E-06 -37.36755355 -20.0741721 -37.3675535 -20.074172
64 -28.7208628
fit.
linear relationship between the two variables. The heavier helmets tend to be less expensive.
ů
The estimated regression equation provided a
60
-
good
bad
b. Does there appear to be any relationship between these two variables?
There appears to be ✓
linear relationship between the two variables. The heavier helmets tend to be less expensive.
c. Develop the estimat negative equation that can be used to predict the price given the weight. Also report the standard error of the estimate,
R-sq, and
positive
R-sq adj.
e. Did the estimated regression equation provide a good fit?
R-sq is
(to 4 decimals).
The estimated regression equation provided
F
d. Test for the significance of the relationship at the .05 level of significance.
P-value is
(to 4 decimals).
that the two variables are related.
ession equation provide a good fit?
4 decimals).
70
fit.
#fit.
USE THE SUMMARY OUTPUT TO ANSWER THE QUESTIONS
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