On rainy days, Joe is late to work with probability .3; on nonrainy days, he is late with probability .1. With probability .7, i
1 answer:
Answer:
a) 76% probability that Joe is early tomorrow.
b) 64.47% conditional probability that it rained
Step-by-step explanation:
We have these following probabilities:
A 70% probability that it will rain tomorrow.
A 30% probability that it does not rain tomorrow.
If it rains, a 30% probability that Joe is late and a 100-30 = 70% probability that Joe is early.
if it does not rain, a 10% probability that Joe is late and a 100-10 = 90% probability that Joe is early.
(a) Find the probability that Joe is early tomorrow.
Either it rains(70% probability) and he is early(70% probability when it rains), or it does not rain(30% probability) and he is early(90% probability when it does not rain). So
76% probability that Joe is early tomorrow.
(b) Given that Joe was early, what is the conditional probability that it rained?
By the Bayes theorem, this probability is:
The probability that it rained and he was early divided by the probability he was early.
Rained and early
70% probability it rains.
70% probability he is early when it rains.
Early
From a), 0.76
Probability
64.47% conditional probability that it rained
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Answer:
<h2> y = 6x - 1</h2>Step-by-step explanation:
(0, -1) ⇒ x₁ = 0, y₁ = -1
(1, 5) ⇒ x₂ = 1, y₂ = 5
So the slope:
The slope-intercept form of the equation of line is y = mx + b, where m is the slope and b is the y-intercept of the line.
(0, -1) ⇒ x₀ = 0, y₀ = -1 ⇒ b = -1
Therefore:
y = 6x - 1 ← the slope-intercept form of the equation
Answer:
The table will be:
x |-2 | -1 | 0 | 1 | 2
y | 1 | 4 | 5 | 4 | 2
Step-by-step explanation:
The function is:
a) The x values of the table is:
x |-2 | -1 | 0 | 1 | 2
So, when x = -2, y will be:
Doing the same with the other x values we have:
The table will be:
x |-2 | -1 | 0 | 1 | 2
y | 1 | 4 | 5 | 4 | 1
I hope it helps you!
