Delta Airlines quotes a flight time of 2 hours, 5 minutes for its flights from Cincinnati toTampa. Suppose we believe that actual flight times are uniformly distributed between 2 hours and 2 hours, 20 minutes.
a. Show the graph of the probability density function for flight time.b. What is the probability that the flight will be no more than 5 minutes late?c. What is the probability that the flight will be more than 10 minutes late?d. What is the expected flight time?

Answer :

Answer:

a) Figure attached

b) [tex] P(X<130 min)= F(130) = \frac{130-120}{20}=0.5[/tex]

c) [tex] P(X>135) =1-P(X<135) = 1- F(135) = 1- \frac{135-120}{20}= 0.25[/tex]

d) [tex] E(X) =\frac{a+b}{2}= \frac{120+140}{2}= 130min[/tex]

Step-by-step explanation:

2 hr = 120 min

2hr 20 min = 120+20 = 140 min

Let X the random variable that represent "flight time". And we know that the distribution of X is given by:

[tex]X\sim Uniform(120 ,140)[/tex]

For this case the density function for A is given by:

[tex] f(X) = \frac{1}{b-a}= \frac{1}{20} , 120\leq X \leq 140 [/tex]

And [tex] f(X)= 0[/tex] for other case

Part a

For this case we can see the figure attached. We see that the probability density function is defined between 120 and 140 minutes.

Part b

The arrival time is 2hr 5 min = 125 min. So then 5 minutes leate means 130 min

For this case we want to find this probability:

[tex] P(X<130 min)[/tex]

And we can use the cumulative distribution function for X given by:

[tex] F(X) = \frac{x-120}{140-120} = \frac{x-120}{20} , 120\leq X \leq 140 [/tex]

And if we use this formula we got:

[tex] P(X<130 min)= F(130) = \frac{130-120}{20}=0.5[/tex]

Part c

For this case more than 10 minutes late means 125 +10 = 135 min or more, so we want this probability:

[tex] P(X>135)[/tex]

And using the complement rule we have:

[tex] P(X>135) =1-P(X<135) = 1- F(135) = 1- \frac{135-120}{20}= 0.25[/tex]

Part d

The expected value for the uniform distribution is given by:

[tex] E(X) =\frac{a+b}{2}= \frac{120+140}{2}= 130min[/tex]

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