Please please please someone help me
2 answers:
You might be interested in
The time taken by the first and the second train is 1 hour 40 minutes and 1 hour 25 minutes. Then the time when the second train at Niles junction is 5:55 p.m.
<h3>What is speed?</h3>The distance covered by the particle or the body in an hour is called speed. It is a scalar quantity. It is the ratio of distance to time.
We know that the speed formula
A train leaves Thorn junction at 1:25 p.m. and arrives in Niles at 3:05 p.m. the train makes two stops along the route for a total of 15 minutes.
A second train leaves Thorn junction at 4:30 p.m. and heads to Niles.
This train does not make any stops.
Let the speed of both trains be equal.
Then the time taken by the first train will be
t₁ = 3:05 p.m. - 1:25 p.m.
t₁ = 1 hour 40 minutes
Then the time taken by the second train will be
t₂ = 1:40 - 00:15
t₂ = 1:25 = 1 hour 25 minutes
The time when the second train is at Niles junction will be
→ 4:30 p.m. + 1:25
→ 5:55 p.m.
More about the speed link is given below.
#SPJ1
Question:
According to Masterfoods, the company that manufactures M&M's, 12% of peanut M&M's are brown, 15% are yellow, 12% are red, 23% are blue, 23% are orange and 15% are green. You randomly select peanut M&M's from an extra-large bag looking for a red candy.
If every student in a large Statistics class selects peanut M&M’s at random until they get a red candy, on average how many M&M’s will the students need to select? (Round your answer to two decimal places.).
Answer:
If every student in the large Statistics class selects peanut M&M’s at random until they get a red candy the expected value of the number of M&M’s the students need to select is 8.33 M&M's.
Step-by-step explanation:
To solve the question, we note that the statistical data presents a geometric mean. That is the probability of success is of the form.
The amount of repeated Bernoulli trials required before n eventual success outcome or
The probability of having a given number of failures before the first success is recorded.
In geometric distribution, the probability of having an eventual successful outcome depends on the the completion of a certain number of attempts with each having the same probability of success.
If the probability of each of the preceding trials is p and the kth trial is the first successful trial, then the probability of having k is given by
Pr(X=k) =
The number of expected independent trials to arrive at the first success for a variable Xis 1/p where p is the expected success of each trial hence p is the probability for the red and the expected value of the number of trials is 1/p or where p = 12 % which is 0.12
1/p = 1/0.12 or 25/3 or 8.33.