Respuesta :
Answer:
(a)
[tex]1-P\big(\frac{X-\mu}{\sigma} < 1.809 \big) = 1 - (0.96477) = 0.03423[/tex]
(b)
[tex]P (z < -1.047) = 0.14755[/tex]
(c)
[tex]P(z \leq 1.238) - P(z \leq -0.47) = 0.89214 - 0.31918 = 0.5729[/tex]
Step-by-step explanation:
The first thing that you need to understand is how the random variable is distributed, it is normally distributed with mean cost [tex]\mu = 370\[/tex] and standard deviation [tex]\sigma = 105\[/tex].
Now for (a)
We are looking for the following probability
[tex]P(X \geq 560)[/tex]
Here is easier to work with the complement of it, so we get
[tex]P(X \geq 560) = 1 - P(X < 560)[/tex]
Now we need to standardize that, for standardization we use the following formula
[tex]1-P\big(\frac{X-\mu}{\sigma} < \frac{560-\mu}{\sigma} \big) = 1-P\big(\frac{X-\mu}{\sigma} < \frac{560-370}{\105} \big) = 1-P\big(\frac{X-\mu}{\sigma} < 1.809 \big)[/tex]
And here you have to grab a standard normal table and see what is that probability.
[tex]1-P\big(\frac{X-\mu}{\sigma} < 1.809 \big) = 1 - (0.96477) = 0.03423[/tex]
Now, if you want to interpret that result in terms of intuition, that means that the event is very unlikely.
(b)
You are looking for the following probability
[tex]P(X \leq 260) = \\\\P\big( \frac{X-\mu}{\sigma} \leq \frac{260-\mu}{\sigma} \big)\\\\ = P\big( \frac{X-\mu}{\sigma} \leq \frac{260-370}{150} \big) \\\\= P (z < -1.047) = 0.14755[/tex]
(c)
You are looking for the following probability
[tex]P(320 \leq X \leq 500) = P\big( \frac{320-370}{105} < z < \frac{500-370}{105} \big) \\\\= P(-0.47 < z<1.2380) = P(z \leq 1.238) - P(z \leq -0.47) = 0.89214 - 0.31918 = 0.5729[/tex]
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