A psychologist read the results of the study and wanted to replicate the methodology in her school. The data are below. Number in class     Number of incidents 10                          120 18                          090 20                          118 19                          060 20                          081 12                          064 15                          026 14                          038 12                          050 11                          080 15                          100 11                          124   12.) The linear equation for the above data is a) Ŷ =84.478X + (-.354) b) Ŷ =-.354X + 84.478 c) Ŷ = -.040X + 84.478 d) Ŷ =1.997X + (-.354)   How many incidents would be expected if there were 17 people in the class ?_________________   What is the coefficent of determination?

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A psychologist read the results of the study and wanted to replicate the methodology in her school. The data are below.

Number in class     Number of incidents

10                          120

18                          090

20                          118

19                          060

20                          081

12                          064

15                          026

14                          038

12                          050

11                          080

15                          100

11                          124

 

12.) The linear equation for the above data is

a) Ŷ =84.478X + (-.354)

b) Ŷ =-.354X + 84.478

c) Ŷ = -.040X + 84.478

d) Ŷ =1.997X + (-.354)

 

How many incidents would be expected if there were 17 people in the class ?_________________

 

What is the coefficent of determination?

Model Summary
R
Adjusted R
Square
Std. Error of
Model
R
Square
the Estimate
Change Statistics
R Square
Change
Sig. F
Change
F
Change
df1 df2
.040°
.002
-.098
34.19266
.002
.016
1
10
.901
a. Predictors: (Constant), Number in class
ANOVA
Model
Sum of Squares df Mean Square
Sig.
18.872 .0161.901"
1 Regression
18.872
1
Residual
11691.378 10
1169.138
Total
11710.250 11
a. Dependent Variable: Number of incidents
b. Predictors: (Constant), Number in class
Coefficients
Standardized
Model
Unstandardized Coefficients
Coefficients
Sig.
B
Std. Error
Beta
1 (Constant)
84.478
1.99
Number in class
-.354
2.789
-.040
-.127 |.901
a. Dependent Variable: Number of incidents
Transcribed Image Text:Model Summary R Adjusted R Square Std. Error of Model R Square the Estimate Change Statistics R Square Change Sig. F Change F Change df1 df2 .040° .002 -.098 34.19266 .002 .016 1 10 .901 a. Predictors: (Constant), Number in class ANOVA Model Sum of Squares df Mean Square Sig. 18.872 .0161.901" 1 Regression 18.872 1 Residual 11691.378 10 1169.138 Total 11710.250 11 a. Dependent Variable: Number of incidents b. Predictors: (Constant), Number in class Coefficients Standardized Model Unstandardized Coefficients Coefficients Sig. B Std. Error Beta 1 (Constant) 84.478 1.99 Number in class -.354 2.789 -.040 -.127 |.901 a. Dependent Variable: Number of incidents
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