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Kipish [7]
2 years ago
11

Difference in elevation between mount Everest and Dead sea

Mathematics
2 answers:
Snowcat [4.5K]2 years ago
5 0

The difference is 27, 735 ft


mariarad [96]2 years ago
5 0
The difference between the two elevations is 30,340 feet.

Mt. Everest, the highest elevation in Asia, is 29,028 feet above sea level. The Dead Sea, the lowest elevation, is 1,312 feet below sea level.
hope this helps!
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At a certain high school, 35 students play only stringed instruments, 10 students play only brass instruments, and 5 students pl
Sophie [7]

Answer:

9/11

Step-by-step explanation:

Well we know there are 55 students in total and only 45 of them can either play a string or brass instrument.

So 45/55 is 9/11

Thus probably is 9/11 of a randomly selected student who plays either a string or brass.

5 0
2 years ago
a swimmer swam 48 kilometers in d days. What is the value of the d if the swimmer swam an average of 3.2 kilometers daily?
lianna [129]
Time= distance/speed

=48/3.2= 15
6 0
3 years ago
Drew has 50 red, green, and blue marbles. He has six more red marbles than blue marbles and four fewer green marbles than blue m
Yanka [14]
Drew has 56 Red Marbles, 56 Green Marbles, Drew has about 60 Blue Marbles. First i added 6 to Red since Red Has 6 More Marbles Than Blue, Then i added Subtracted 4 from green, which resulted in 46 Green Marbles. Finally i added 4 and 6 to get 60 Blue Marbles. I am not sure if i am correct, but i gave it a shot! ^-^
4 0
2 years ago
in sports club there are 800 members . the ratio of soccer members to social members is 5to 3 how many soccer players are there
attashe74 [19]
5:3

5+3=8
8 units

800=8 units
divide oth sides by 8
100=1 units

soccer=5 units=5 times 100=500
social=3 units=3 times 100=300



500 soccer players

5 0
2 years ago
Lie detectors have a 15% chance of concluding that a person is lying even when they are telling the truth. a bank conducts inter
Otrada [13]
Part A:

Given that lie <span>detectors have a 15% chance of concluding that a person is lying even when they are telling the truth. Thus, lie detectors have a 85% chance of concluding that a person is telling the truth when they are indeed telling the truth.

The case that the lie detector correctly determined that a selected person is saying the truth has a probability of 0.85
Thus p = 0.85

Thus, the probability that </span>the lie detector will conclude that all 15 are telling the truth if <span>all 15 applicants tell the truth is given by:

</span>P(X)={ ^nC_xp^xq^{n-x}} \\  \\ \Rightarrow P(15)={ ^{15}C_{15}(0.85)^{15}(0.15)^0} \\  \\ =1\times0.0874\times1=0.0874
<span>

</span>Part B:

Given that lie detectors have a 15% chance of concluding that a person is lying even when they are telling the truth. Thus, lie detectors have a 85% chance of concluding that a person is telling the truth when they are indeed telling the truth.

The case that the lie detector wrongly determined that a selected person is lying when the person is actually saying the truth has a probability of 0.25
Thus p = 0.15

Thus, the probability that the lie detector will conclude that at least 1 is lying if all 15 applicants tell the truth is given by:

P(X)={ ^nC_xp^xq^{n-x}} \\ \\ \Rightarrow P(X\geq1)=1-P(0) \\  \\ =1-{ ^{15}C_0(0.15)^0(0.85)^{15}} \\ \\ =1-1\times1\times0.0874=1-0.0874 \\  \\ =0.9126


Part C:

Given that lie detectors have a 15% chance of concluding that a person is lying even when they are telling the truth. Thus, lie detectors have a 85% chance of concluding that a person is telling the truth when they are indeed telling the truth.

The case that the lie detector wrongly determined that a selected person is lying when the person is actually saying the truth has a probability of 0.15
Thus p = 0.15

The mean is given by:

\mu=npq \\  \\ =15\times0.15\times0.85 \\  \\ =1.9125


Part D:

Given that lie detectors have a 15% chance of concluding that a person is lying even when they are telling the truth. Thus, lie detectors have a 85% chance of concluding that a person is telling the truth when they are indeed telling the truth.

The case that the lie detector wrongly determined that a selected person is lying when the person is actually saying the truth has a probability of 0.15
Thus p = 0.15

The <span>probability that the number of truthful applicants classified as liars is greater than the mean is given by:

</span>P(X\ \textgreater \ \mu)=P(X\ \textgreater \ 1.9125) \\  \\ 1-[P(0)+P(1)]
<span>
</span>P(1)={ ^{15}C_1(0.15)^1(0.85)^{14}} \\  \\ =15\times0.15\times0.1028=0.2312<span>
</span>
8 0
3 years ago
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