Code: 13A05305
R13
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD
B. Tech II Year I Semester Examinations, November/December - 2016
PROBABILITY AND STATISTICS
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(Common to EEE, ECE, CSE, EIE, ETM)
Time: 3 Hours Max. Marks: 75
Note: This question paper contains two parts A and B.
Part A is compulsory which carries 25 marks. Answer all questions in Part A. Part B consists of 5 Units. Answer any one full question from each unit. Each question carries 10 marks.
PART - A (25 Marks)
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- If two cards are drawn from a deck of cards what is the probability that both will be diamonds? [2M]
- Define conditional probability. [3M]
- A random variable X has density function f(x) = kx2, 0 = x = 1, find k. [2M]
- Define moment generating function. [3M]
- Define critical region. [2M]
- Write properties of good estimator. [3M]
- Write the applications of t-distribution. [2M]
- Write about Type-I and Type-II errors. [3M]
- Define stochastic process. [2M]
- Define transient and recurrent state. [3M]
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PART - B (50 Marks)
(Answer all five units, choosing one question from each unit)
UNIT - I
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2.a) State and prove Baye’s theorem. [5M]
b) Two dice are thrown. Find the probability that (i) the sum is greater than 8 and (ii) the sum is neither 7 nor 11. [5M]
OR
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3.a) A problem in mathematics is given to three students whose chances of solving it are 1/2, 1/3, 1/4 respectively. What is the probability that the problem is solved? [5M]
b) If A and B are independent events, prove that Ac and Bc are also independent events. [5M]
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UNIT - II
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4.a) A continuous random variable has probability density function f(x) given by f(x) = { kx, 0 = x = 2; 2k, 2 = x = 4; -kx + 6k, 4 = x = 6 }. Find k and mean value of X. [5M]
b) The number of monthly breakdown of a computer is a random variable having a Poisson distribution with mean equal to 1.8. Find the probability that this computer will function without a breakdown during a month. [5M]
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OR
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5.a) Define distribution function and state its properties. [5M]
b) Out of 800 families with 4 children each, how many families would be expected to have (i) 2 boys and 2 girls (ii) atleast one boy (iii) no girl (iv) atmost two girls. Assume equal probabilities for boys and girls. [5M]
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UNIT - III
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6.a) A population consists of 5 numbers 2, 3, 6, 8 and 11. Consider all possible samples of size 2 which can be drawn with replacement from the population. Find [5M]
- the mean of the population
- the standard deviation of the population
- the mean of the sampling distribution of means
- the standard deviation of the sampling distribution of means
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b) State and prove central limit theorem. [5M]
OR
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7.a) Find 95% confidence limits for the mean of a population from which the following sample was taken 15, 17, 10, 18, 16, 9, 7, 11, 13, 14. [5M]
b) Explain the terms: (i) Null hypothesis (ii) Alternative hypothesis (iii) Critical region (iv) Level of significance. [5M]
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UNIT - IV
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8.a) Explain the procedure of testing of hypothesis. [5M]
b) A random sample of size 16 values from a normal population showed a mean of 53 and a sum of squares of deviations from the mean equals to 150. Can it be regarded as taken from the population having 56 as mean? Obtain 95% confidence limits of the mean of the population. [5M]
OR
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9.a) Two random samples are drawn from two normal populations are [5M] Sample 1: 20, 16, 26, 27, 23, 22, 18, 24, 25, 19 Sample 2: 27, 33, 42, 35, 32, 34, 38, 28, 41, 43 Test whether the populations have the same variance.
b) The following are the number of mistakes made in 5 successive days by 4 technicians working for a service department of a company. [5M]
Technician: A B C D
Mistakes: 1 3 4 6
2 4 6 9
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3 6 5 11
4 5 7 10
5 6 8 11
Test whether the difference among the four technicians is significant.
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UNIT - V
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10.a) Define Markov chain. Explain its properties. [5M]
b) A fair die is tossed repeatedly. If Xn denotes the maximum of the numbers occurring in the first n tosses, find the transition probability matrix P of the Markov chain {Xn}. [5M]
OR
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11.a) Explain queuing model M/M/1: 8 / FIFO. [5M]
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b) Obtain the steady state probabilities of Markov chain with transition probability matrix P = [ 0 1
1/2 1/2 ] . [5M]
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