Answer:
13
Step-by-step explanation:
I believe I answered a similar question, the reasoning behind it is the same.
Answer:
Step-by-step explanation:
Hello!
Given the variables
Y: standardized history test score in third grade.
X₁: final percentage in history class.
X₂: number of absences per student.
<em>Determine the following multiple regression values.</em>
I've estimated the multiple regression equation using statistics software:
^Y= a + b₁X₁ + b₂X₂
a= 118.68
b₁= 3.61
b₂= -3.61
^Y= 118.68 + 3.61X₁ - 3.61X₂
ANOVA Regression model:
Sum of Square:
SS regression: 25653.86
SS Total: 36819.23
F-ratio: 11.49
p-value: 0.0026
Se²= MMError= 1116.54
Hypothesis for the number of absences:
H₀: β₂=0
H₁: β₂≠0
Assuming α:0.05
p-value: 0.4645
The p-value is greater than the significance level, the decision is to not reject the null hypothesis. Then at 5% significance level, there is no evidence to reject the null hypothesis. You can conclude that there is no modification of the test score every time the number of absences increases one unit.
I hope this helps!
2 Dimensional shape with 5 obtuse angle is <em>Pentagon.</em>
Answer:
18
Step-by-step explanation:
3 times 3 equals 9
9 times 2 equals 18
