Customer arrivals at a fast-food outlet conform to a Poisson distribution with an average rate of 16 customers per hour. In statistical probability analysis, the Poisson distribution is a commonly utilized discrete probability distribution. Employing the formula, it has been calculated that 0.0661 represents the probability of there being precisely 12 arrivals in the next hour.
Answer:
The outcomes are listed below.
Step-by-step explanation:
Only the differential costs will be considered. Therefore, the costs associated with sugar beets and their processing are not relevant to the decision.
Beet fiber:
Sold as is for $25
Continued processing yields = 57 - 16= $41
It is more favorable to further process the beet fiber.
Beet juice:
Sold as is for $39
Continued processing yields = 84 - 22= $62
Continuing the processing of beet juice is also more advantageous.
An equation of the form
describes a line
that passes through the origin and whose tangent corresponds to
. Generally, any equation formatted as
represents a line.
We start with the following information:
p = probability = 0.12<span>
n = total number of students = 39 </span>
x = number of left-handers = 5<span>
u = mean = p * n = 4.68
σ = standard deviation = √(n*p*(1-p)) = √(39 * 0.12 * 0.88) =
2.03</span>
Finding the z score:
z = (x – u) / σ
<span>
z = (5 – 4.68) / 2.03
</span>
z
= 0.1576 = 0.16
<span>
</span>Applying standard tables for z gives the p value as:
p value = 0.5636 = 56.36%
Consequently, there is a 56.36% probability.
Answer:
The solution yields a number equal to -136.
Step-by-step explanation:
Let x represent the number, leading to the following equation:
x + 2 = 7/8 x - 15
Rearranging gives:
x - 7/8 x = -15 - 2
1/8 x = -17
x = -17 * 8 resulting in -136.
