Answer:
The probability of missing the first metal-carrying person is P(x≤50)=0.395
Step-by-step explanation:
We define as success to: missing metal carrying detection.
p=0.01
P(x)=
We look for the probability when all metal carring people is detected so x=0
P(x≤50)=1-P(x=0)=
=0.395
Blank 1: 3
Blank 2: 27
Blank 3: 21
you have to distribute the three to everything inside the parenthesis, and because it's directly in front of the parenthesis it's being multiplied.
3(x - 9) = 3x - 27
Now you need to isolate the y, in this e ample you need to add 6 to both sides
the final equation should be:
y = 3x - 21
Answer:
(a) The expected number of should a salesperson expect until she finds a customer that makes a purchase is 0.9231.
(b) The probability that a salesperson helps 3 customers until she finds the first person to make a purchase is 0.058.
Step-by-step explanation:
Let<em> </em>the random variable <em>X</em> be defined as the number of customers the salesperson assists before a customer makes a purchase.
The probability that a customer makes a purchase is, <em>p</em> = 0.52.
The random variable <em>X</em> follows a Geometric distribution since it describes the distribution of the number of trials before the first success.
The probability mass function of <em>X</em> is:

The expected value of a Geometric distribution is:

(a)
Compute the expected number of should a salesperson expect until she finds a customer that makes a purchase as follows:


This, the expected number of should a salesperson expect until she finds a customer that makes a purchase is 0.9231.
(b)
Compute the probability that a salesperson helps 3 customers until she finds the first person to make a purchase as follows:

Thus, the probability that a salesperson helps 3 customers until she finds the first person to make a purchase is 0.058.
Answer:
D. x = 5
Step-by-step explanation:
At x = 5
y = -½(5)²
y = -½ × 25 = -25/2 = -12½