82 44 F 80 40 80 40 H. 79 38 74 28 70 60 's use basic stats to create regression equation (which we already know, but do i E.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Correlations
Pearson Correlation
444
Sig. (2-tailed)
.199
10
10
y
Pearson Correlation
444
1
Sig. (2-tailed)
.199
N
10
10
Descriptive Statistics
Mean
Std. Deviation
10
83.40
9.009
10
46.70
18.185
Valid N (listwise)
10
Transcribed Image Text:Correlations Pearson Correlation 444 Sig. (2-tailed) .199 10 10 y Pearson Correlation 444 1 Sig. (2-tailed) .199 N 10 10 Descriptive Statistics Mean Std. Deviation 10 83.40 9.009 10 46.70 18.185 Valid N (listwise) 10
Compute predicted Y and residual scores.
Regression equation: Y' = -28.0 + .9x
Person
X
Y
Y'
Resid
A
100
80
B
93
66
90
19
D
86
52
E
82
44
80
40
G
80
40
H
79
38
74
28
70
60
Let's use basic stats to create regression equation (which we already know, but do it anyway)
Y' =
LL
Transcribed Image Text:Compute predicted Y and residual scores. Regression equation: Y' = -28.0 + .9x Person X Y Y' Resid A 100 80 B 93 66 90 19 D 86 52 E 82 44 80 40 G 80 40 H 79 38 74 28 70 60 Let's use basic stats to create regression equation (which we already know, but do it anyway) Y' = LL
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