Probability

Question 1
Suppose p is the number of cars per minute passing through a certain road junction between 5 PM and 6 PM, and p has a Poisson distribution with mean 3. What is the probability of observing fewer than 3 cars during any given minute in this interval?
Cross
8 / (2e3)
Cross
9 / (2e3)
Tick
17 / (2e3)
Cross
26 / (2e3)


Question 1-Explanation: 
See http://en.wikipedia.org/wiki/Poisson_distribution#Definition
PR(X < 3) = Pr(x = 0) + Pr(x = 1) + Pr(x = 2) = f(0, 3) + f(1, 3) + f(2, 3) Put \\lambda = 3 and k = 0, 1, 2 in the formula given at http://en.wikipedia.org/wiki/Poisson_distribution#Definition = 17 / (2e3)
Question 2
Out of all the 2-digit integers between 1 and 100, a 2-digit number has to be selected at random. What is the probability that the selected number is not divisible by 7?
Cross
13/90
Cross
12/90
Cross
78/90
Tick
77/90


Question 2-Explanation: 
There are total 90 two digit numbers, out of them 13 are divisible by 7, these are 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, 84, 91, 98. Therefore, probability that selected number is not divisible by 7 = 1 - 13/90 = 77/90. So, option (D) is true.
Question 3
Suppose a fair six-sided die is rolled once. If the value on the die is 1, 2, or 3, the die is rolled a second time. What is the probability that the sum total of values that turn up is at least 6?
Cross
10/21
Tick
5/12
Cross
2/3
Cross
1/6


Question 3-Explanation: 

Solution set: { 6, (1,5), (1,6) ......}

                  i.e. P(6 appeared on first throw) +

                       P(1 appeared on first throw and 5 appeared on second throw) +

                        P(1 appeared on first throw and 6 appeared on second throw) + ....................

                      = 1/6 + (1/6)(1/6) + (1/6)(1/6) + .....

                      = 1/6 + 9/36

                      = 5/12.

Viewpoint 2:

P(......) =   P(6 came on first throw) +  P(sum>= 6 and 1,2,3 appeared in first throw)

          =      1/6                                +                 ????

P(1,2,3 appeared in first throw) = 1/2                                                   //P(E1)

P(sum >= 6 | 1,2,3 appeared in first throw) = 9/18                             //P(E2 | E1)

// Our new sample space is:  { (1,1), (1,2), (1,3), (1,4), (1,5), (1,6)

                                                 (2,1), (2,2), (2,3), (2,4), (2,5), (2,6)

                                                (3,1), (3,2), (3,3), (3,4), (3,5), (3,6) }

// 9 favorable cases: {(1,5), (1,6), (2,4), (2,5), (2,6), (3,3), (3,4), (3,5), (3,6) }

P(sum>= 6 and 1,2,3 appeared in first throw) = (1/2)(9/18)              //P(E2 ∩ E1) = P(E1)P(E2|E1)

P(what we are looking for) = 1/6 + 9/36     = 5/12

Correct Answer: B

Question 4
Consider a random variable X that takes values +1 and −1 with probability 0.5 each. The values of the cumulative distribution function F(x) at x = −1 and +1 are
Cross
0 and 0.5
Cross
0 and 1
Tick
0.5 and 1
Cross
0.25 and 0.75


Question 4-Explanation: 
The Cumulative Distribution Function F(x) = P(X≤x) F(-1) = P(X≤-1) = P(X=-1) = 0.5 F(+1) = P(X≤+1) = P(X=-1) + (P=+1) = 0.5+0.5 = 1
Question 5
If two fair coins are flipped and at least one of the outcomes is known to be a head, what is the probability that both outcomes are heads?
Tick
1/3
Cross
1/4
Cross
1/2
Cross
2/3


Question 5-Explanation: 
Since we know one outcome is head, there are only three possibilities {h, t}, {h, h}, {t, h} The probability of both heads = 1/3
Question 6
If the difference between expectation of the square of a random variable (E[X²]) and the square of the expectation of the random variable (E[X])² is denoted by R, then?
Cross
R = 0
Cross
R < 0
Tick
R >= 0
Cross
R > 0


Question 6-Explanation: 
The difference between  (E[X²]) and (E[X])² is called variance of a random variable.  Variance measures how far a set of numbers is spread out. (A variance of zero indicates that all the values are identical.) A non-zero variance is always positive:
Question 7
Consider a finite sequence of random values X = { x1, x2,..., xn}. Let μx be the mean and σx be the standard deviation of X. Let another finite sequence Y of equal length be derived from this as yi = a*xi + b, where a and b are positive constants. Let μy be the mean and σy be the standard deviation of this sequence. Which one of the following statements is INCORRECT?
Cross
Index position of mode of X in X is the same as the index position of mode of Y in Y.
Cross
Index position of median of X in X is the same as the index position of median of Y in Y.
Cross
μy = aμx+b
Tick
σy = aσx+b


Question 7-Explanation: 
Adding a constant like b shift the distribution while multiplying to a constant like a stretch the distribution along median \"gate2011A29\" Mode is the most frequent data of the distribution, so the index position of the mode will not change. From the above graph it is clear that index position of the median will also not change. Now for the mean  Y_{i} = a X_{i} + b \\newline \\newline \\sum Y_{i}  = \\sum(aX-{i} + b) \\newline  \\sum Y_{i} = a(\\sum X_{i}) + nb \\newline (\\sum Y_{i})/n = a(\\sum X_{i})/n + b \\newline \\mu _{y} = a\\mu_{x} + b  And for the standard deviation  \\newline \\newline \\sigma _{y} = \\sqrt{\\frac{1}{n} \\sum (\\mu_{y} - Y_{i})^{2}} \\newline \\newline \\sigma _{y} = \\sqrt{\\frac{1}{n} \\sum (a\\mu_{x} + b - Y_{i})^{2}} \\newline \\sigma _{y} = \\sqrt{\\frac{1}{n} \\sum (a\\mu_{x} + b - aX_{i} - b)^{2}} \\newline \\newline \\sigma _{y} = \\sqrt{\\frac{1}{n} \\sum (a\\mu_{x} - aX_{i} )^{2}} \\newline \\newline \\sigma _{y} = a\\sqrt{\\frac{1}{n} \\sum (\\mu_{x} - X_{i} )^{2}} \\newline \\newline \\sigma _{y} = a\\sigma_{x}     
Question 8
Consider a company that assembles computers. The probability of a faulty assembly of any computer is p. The company therefore subjects each computer to a testing process.This testing process gives the correct result for any computer with a probability of q. What is the probability of a computer being declared faulty?
Tick
pq + (1 - p)(1 - q)
Cross
(1 - q) p
Cross
(1 - p) q
Cross
pq


Question 8-Explanation: 
A computer can be declared faulty in two cases 
1) It is actually faulty and correctly declared so (p*q)
2) Not faulty and incorrectly declared (1-p)*(1-q). 
Question 9
What is the probability that divisor of 1099 is a multiple of 1096?
Tick
1/625
Cross
4/625
Cross
12/625
Cross
16/625


Question 9-Explanation: 
Following are multiples of 1096 which are also divisor of 1099 1096, 2x1096, 4x1096, 5x1096, 8x1096, 10x1096, 20x1096, 25x1096, 40x1096, 50x1096, 100x1096, 125x1096, 200x1096, 250x1096, 500x1096, 1000x1096 The total number of divisors of 1099 = 10000  (See http://www.math.cmu.edu/~mlavrov/arml/13-14/number-theory-09-29-13.pdf) So the probability = 16/10000 = 1/625
Question 10
An unbalanced dice (with 6 faces, numbered from 1 to 6) is thrown. The probability that the face value is odd is 90% of the probability that the face value is even. The probability of getting any even numbered face is the same. If the probability that the face is even given that it is greater than 3 is 0.75, which one of the following options is closest to the probability that the face value exceeds 3?
Cross
0.453
Tick
0.468
Cross
0.485
Cross
0.492


Question 10-Explanation: 
Let Xi be the probability that the face value is i. We can say that,
X1 + X2 + X3 + X4 + X5 + X6 = 1 
It is given that,
(X1 + X3 + X5) = 0.9*(X2 + X4 + X6) 
It is also given that,
X2 = X4 = X6 
Also given that,
(X4 + X6)/(X4 + X5 + X6) = 0.75 
Solving the above equations, we can get,
X4 + X5 + X6 = 0.468 
So, option (B) is correct. Improvement done by maninuthi.
There are 93 questions to complete.

  • Last Updated : 21 Jan, 2014

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