Well, Branlycom,
In mathematical terms, situation usually means a synonym for the whole equation. (Keep in mind that synonym means "alike/same".)
↑ ↑ ↑ Hope this helps! :D
Answer:
<h3>
Step-by-step explanation:</h3>
The z-value is computed from ...
... z = (x -µ)/σ
... z = (184 -206)/10 = -2.2 . . . . for $184
... z = (200 -206)/10 = -0.6 . . . . for $200
You can look up these values in a normal distribution table, or you can use an appropriate calculator to find the corresponding percentiles.
... -2.2 corresponds to the 1.390 percentile. (That amount of area is below -2.2 standard deviations from the mean.)
... -0.6 corresponds to the 27.425 percentile.
Subtracting the two percentages gives the percentage of expenses between $184 and $200. That number is 26.035% ≈ 26%.
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<em>Comment on the calculator display</em>
The difference that got cut off from the display in the attachment is ...
... 0.2603496703
The <em>normalcdf( )</em> function requires a lower limit. Using -8 standard deviations is effectively equivalent to -∞ for this purpose, as any lower number has no effect on the least-significant digits of the result.
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:

And we can assume a normal distribution and then we can solve the problem with the z score formula given by:

And replacing we got:


We can find the probability of interest using the normal standard table and with the following difference:

Step-by-step explanation:
Let X the random variable who represent the expense and we assume the following parameters:

And for this case we want to find the percent of his expense between 38.6 and 57.8 so we want this probability:

And we can assume a normal distribution and then we can solve the problem with the z score formula given by:

And replacing we got:


We can find the probability of interest using the normal standard table and with the following difference:
