Answer:
No, the points are in a linear pattern.
Step-by-step explanation:
Residual plot is a graph that shows the residuals on the vertices. The y-axis has residual values and x-axis has independent variables. The horizontal axis shows the independent variables to determine the best fit for a set. The graph given is in a linear pattern. The random pattern shows that linear model is good fit.
Answer:
39.10%
Step-by-step explanation:
The given timeout distributions are:
Exp (1/10), Exp (1/12)
The equation to use is the following:
F (x) = 1 - e ^ (- a / b); x> 0
So the probability is:
P (food has not arrived after waiting 25 minutes | R) = e ^ (- 10/10) = 0.3679
P (food has not arrived after waiting 25 minutes | S) = e ^ (- 12/15) = 0.2865
So:
P (food has not arrived after waiting 25 minutes) = (food has not arrived after waiting 25 minutes | R) * P (R) + (food has not arrived after waiting 25 minutes | S) * P (S)
Replacing:
P (food has not arrived after waiting 25 minutes) = 0.3679 * 1/3 + 0.2865 * 2/3 = 0.3136
However:
P (R | food has not arrived after waiting 25 minutes) = (food has not arrived after waiting 25 minutes | R) * P (R) / P (food has not arrived after waiting 25 minutes)
P (R | food has not arrived after waiting 25 minutes) = 0.3679 * 1/3 / 0.3136 = 0.3910
It means that the probability is 39.10%
I would’ve guess it’s 10+20=10+20 since you didn’t show no pic :|
Answer:
6 * 42 = 6 * (20 + 22)
= (6 * 20) + (6 * 22) = 120 + 132 = 252
Step-by-step explanation:
Here, we want to multiply 6 by 42 using distributive property
In this case, we can have the distributive property as;
a * ( b + c) = ab + bc
Thus, we can represent 42 as (20 + 22)
so 6 * 42 becomes 6 * (20 + 22)
Using the distributive property, we have
(6 * 20) + (6 * 22)
= 120 + 132 = 252
