Answer:
0.6
Step-by-step explanation:
Given the regression equation :
y = 0.2x + 3,
The actual value of y when x = 5 is 4.6
The predicted of y using the model when x = 5 is :
Put x = 5 in the equation :
y = 0.2(5) + 3
y = 1 + 3
y = 4
The error in the value of y predicted is :
Error = Actual value - Predicted value
Error = 4.6 - 4
Error = 0.6
Answer:
16. =
17. <
18. <
Step-by-step explanation:
Answer:
Step-by-step explanation:
Given that Z is a standard normal variate.
We are to calculate the probabilities as given
F(z) represents the cumulative probability i.e. P(Z<z)
a. P(z ≤ −1)
=F(-1)
= 0.158655
b. P(z > .95)
= 1-F(0.95)
= 0.1711
c. P(z ≥ −1.5)
= 1-F(-1.5)
= 0.9332
d. P(−.5 ≤ z ≤ 1.75)
=F(1.75)-F(-0.5)
= 0.6514
e. P(1 < z ≤ 3)
=F(3)-F(1)
=0.1573
Answer:
3. A=40
B= 80
C= 48
4. A= 54
This all i can figure out rn
Step-by-step explanation:
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