The waiting time at which 10 percent of the people would continue to hold is given as 2.3
<h3>How to solve for the waiting time</h3>
We have to solve for X ~ Exponential(λ).
then E(X) = 1/λ = 3,
= 0.3333
Remember that the cumulative distribution function of X is F(x) = 1 - e^(-λx). ; x is equal to the time in over case
For 10 percent of the people we would have a probability of
10/100 = 0.1
we are to find
P(X ≤ t)
= 1 - e^(0.3333)(t) = 0.1
Our concern is the value of t
Then we take the like terms
1-0.1 = e^(0.3333)(t)
1/0.9 = e^(0.3333)(t)
t = 3 * ln(1/0.9)
= 0.3157
The reason for a bimodel distribution is that a bimodal distribution may occasionally result from merging data from two processes or populations.
<h3>What is a bimodel distribution?</h3>
- Two modes comprise a bimodal distribution. In other words, the results of two distinct processes are integrated into a single collection of data.
- The distribution sometimes goes by the name "double-peaked." Consider the distribution of production data over two shifts in a manufacturing facility.
- Bimodal distributions frequently happen as a result of underlying events.
- A bimodal distribution, for instance, can be seen in the amount of patrons who visit a restaurant each hour because people typically eat out for lunch and dinner.
- The bimodal distribution is brought on by the underlying human behavior.
- If a data set has two modes, it is bimodal. This indicates that no particular data value has the highest frequency of occurrence. Instead, the highest frequency is tied between two data values.
Learn more about bimodel distribution here:
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Answer:
$686,000
Explanation:
net service revenue = gross revenue - discount for early payment
gross revenue = total sales price - trade discount
gross revenue = $800,000 - $100,000 = $700,000
net service revenue = $700,000 - 2%($700,000) = $700,000 - $14,000 = $686,000
Answer:
true is the correct answer right
Answer:
False.
You don't want to work day and night, or do something you are not willing to, just to get a bunch of money
Explanation:
