13. Suppose that a certain examination is to be taken by five students independently of one another, and the num- ber of minutes required by any particular student to com- plete the examination has the exponential distribution for which the mean is 80. Suppose that the examination be- gins at 9:00 AM. Determine the probability that at least one of the students will complete the examination before 9:40 A.M.

Q: The question is attached

A:

Q: 1/x

A:

Q: Grafthe fallawing ustion yinhd ラ2エ55 2 1T

A: we use Trigonometry table to find out values of y = sin(2x)

Q: 2. V686

A:

Q: b. 14C11

A: nCr=n!r!×(n−r)!r!=r(r-1)(r-2)×....×3×2×1

Q: 6.5+ 4

A: To simplify given

Q: 3.546 is of 10

A:

Q: 13 dと 2) xp 7-x2

A: Here we have to find the integral value.

Q: 41 21°

A: As we know that  sin(θ)=opposite hypotanuse

Q: Rang lertex = (-7;3) qu'od

A: The quadratic function has vertex (-2,3) and a point on graph 1, 12

Q: 10 + 2/4 = O 20 O 5 O 10

A:

Q: ex- 12

A: Given: y=ex-12 we know that am-n=aman

Q: 4. Find the 2"

A: Given problem is :

Q: Express 5 years and 7 months in months. months

A:

Q: I'm lost

A:

Q: 22+22+88/8=

A: Solution is given below:

Q: 2 questions in pictures

A:

Q: 7 to the power of 18

A: To determine: 7 to the power of 18

Q: Evaluate Lt

A:

Q: OPPO F11 Pro

A: 7C4 =?

Q: 27+2548+432+9=?

A: Given that the expression is

Q: 2. Evaluate dz.

A: I = ∫x31 - x2 dxLet, x = cosθ ⇒ dx = -sinθ dθSo, I = ∫cos3θ1 - cos2θ- sinθ dθ          = - ∫cos3θ…

Q: e

A: We need to evaluate integral.

Q: BCD???

A: Given problems:- b) ∫6w3+7wdwc) ∫y+14ydy d)∫123z-24dz

Q: 4P3

A:

Q: | 2 0.32

A: The given distribution is, X 2 3 4 P(X) 0.32 0.48 0.20

Q: 3. Evaluate

A: The given integral is 1/(x-1)2/3 limit from 0 to 3.

Q: step 1 wrong

A:

Q: Xx well l defned

A:

Addition Rule of Probability

It simply refers to the likelihood of an event taking place whenever the occurrence of an event is uncertain. The probability of a single event can be calculated by dividing the number of successful trials of that event by the total number of trials.

Expected Value

When a large number of trials are performed for any random variable ‘X’, the predicted result is most likely the mean of all the outcomes for the random variable and it is known as expected value also known as expectation. The expected value, also known as the expectation, is denoted by: E(X).

Probability Distributions

Understanding probability is necessary to know the probability distributions. In statistics, probability is how the uncertainty of an event is measured. This event can be anything. The most common examples include tossing a coin, rolling a die, or choosing a card. Each of these events has multiple possibilities. Every such possibility is measured with the help of probability. To be more precise, the probability is used for calculating the occurrence of events that may or may not happen. Probability does not give sure results. Unless the probability of any event is 1, the different outcomes may or may not happen in real life, regardless of how less or how more their probability is.

Basic Probability

The simple definition of probability it is a chance of the occurrence of an event. It is defined in numerical form and the probability value is between 0 to 1. The probability value 0 indicates that there is no chance of that event occurring and the probability value 1 indicates that the event will occur. Sum of the probability value must be 1. The probability value is never a negative number. If it happens, then recheck the calculation.