Using the SPSS output above, what is the value of the coefficient of determination? 0.715 0.846 0.347 2.82

Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter3: Functions And Graphs
Section3.5: Graphs Of Functions
Problem 44E
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30. Using the SPSS output above, what is the value of the coefficient of determination?
0.715
0.846
0.347
O 2.82
Transcribed Image Text:30. Using the SPSS output above, what is the value of the coefficient of determination? 0.715 0.846 0.347 O 2.82
Section H: Hyla chrysoscelis is a type of gray tree frog with a distinct mating call. Frogs are cold-blooded animals, and
their physiology is affected by variations in temperature. Researchers wanted to know if the mating song of Hyla
chrysoscelis is affected by the temperature of its natural habitat. They observed the mating song frequency (y in
notes/sec) and the habitat (x in °Celsius) of 20 Hyla chrysoscelis in the wild. We aim to express the relationship between
and y by using the simple linear regression model Yį = ßo + ß₁ x; + Eį.
Table H.1
Coefficients
Standardized
Unstandardized Coefficients
Coefficients
95.0% Confidence Interval for B
Lower Bound
B
Std. Error
Beta
Sig.
Upper Bound
Model
1
(Constant)
-6.190
-23.508
11.128
Temperature
2.331
1.602
3.059
a. Dependent Variable: Frequency
Table H.2
Model Summary
Model
R Square
R
.846ª
1
.715
a. Predictors: (Constant), Temperature
b. Dependent Variable: Frequency
Adjusted R
Square
8.243
.347
.699
Std. Error of
the Estimate
2.82159
.846
t
-.751
6.721
.462
.000
Transcribed Image Text:Section H: Hyla chrysoscelis is a type of gray tree frog with a distinct mating call. Frogs are cold-blooded animals, and their physiology is affected by variations in temperature. Researchers wanted to know if the mating song of Hyla chrysoscelis is affected by the temperature of its natural habitat. They observed the mating song frequency (y in notes/sec) and the habitat (x in °Celsius) of 20 Hyla chrysoscelis in the wild. We aim to express the relationship between and y by using the simple linear regression model Yį = ßo + ß₁ x; + Eį. Table H.1 Coefficients Standardized Unstandardized Coefficients Coefficients 95.0% Confidence Interval for B Lower Bound B Std. Error Beta Sig. Upper Bound Model 1 (Constant) -6.190 -23.508 11.128 Temperature 2.331 1.602 3.059 a. Dependent Variable: Frequency Table H.2 Model Summary Model R Square R .846ª 1 .715 a. Predictors: (Constant), Temperature b. Dependent Variable: Frequency Adjusted R Square 8.243 .347 .699 Std. Error of the Estimate 2.82159 .846 t -.751 6.721 .462 .000
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