- •Introduction
- •Basic concepts of probability theory
- •Classical definition of probability
- •Relative frequency
- •Geometric probabilities
- •Glossary
- •Exercises for Seminar 1
- •Exercises for Homework 1
- •Basic formulas of combinatorial analysis
- •Operations over events
- •Glossary
- •Exercises for Seminar 2
- •Exercises for Homework 2
- •Theorem of addition of probabilities of incompatible events
- •Complete group of events
- •Opposite events
- •Conditional probability
- •Theorem of multiplication of probabilities
- •Glossary
- •Exercises for Seminar 3
- •Exercises for Homework 3
- •Independent events
- •Where a is the appearance of at least one of the events a1, a2, …, An; .
- •Glossary
- •Exercises for Seminar 4
- •Exercises for Homework 4
- •Theorem of addition of probabilities of compatible events
- •Formula of total probability
- •Probability of hypotheses. Bayes’s formulas.
- •Glossary
- •Exercises for Seminar 5
- •Exercises for Homework 5
- •Repetition (recurrence) of trials. The Bernoulli formula
- •Local theorem of Laplace
- •Integral theorem of Laplace
- •Glossary
- •Exercises for Seminar 6
- •Exercises for Homework 6
- •Random variables. The law of distribution of a discrete random variable
- •A random variable is understood as a variable which as result of a trial takes one of the possible set of its values (which namely – it is not beforehand known).
- •Mathematical operations over random variables
- •(Mathematical) expectation of a discrete random variable
- •Dispersion of a discrete random variable
- •Glossary
- •Exercises for Seminar 7
- •Exercises for Homework 7
- •Distribution function of a random variable
- •Properties of a distribution function
- •Continuous random variables. Probability density
- •Properties of probability density
- •Glossary
- •Exercises for Seminar 8
- •Exercises for Homework 8
- •Basic laws of distribution of discrete random variables
- •1. Binomial law of distribution
- •2. The law of distribution of Poisson
- •3. Geometric distribution
- •4. Hypergeometric distribution
- •Glossary
- •Exercises for Seminar 9
- •Exercises for Homework 9
- •Basic laws of distribution of continuous random variables
- •1. The uniform law of distribution
- •2. Exponential law of distribution
- •3. Normal law of distribution
- •Glossary
- •Exercises for Seminar 10
- •Exercises for Homework 10
- •The law of large numbers and limit theorems
- •The central limit theorem
- •Glossary
- •Exercises for Seminar 11
- •Exercises for Homework 11
- •Mathematical statistics. Variation series and their characteristics
- •Numerical characteristics of variation series
- •Glossary
- •Exercises for Seminar 12
- •Exercises for Homework 12
- •Bases of the mathematical theory of sampling
- •Glossary
- •Exercises for Seminar 13
- •Exercises for Homework 13
- •Methods of finding of estimations
- •Notion of interval estimation
- •Glossary
- •Exercises for Seminar 14
- •Exercises for Homework 14
- •Testing of statistical hypotheses
- •Glossary
- •Exercises for Seminar 15
- •Exercises for Homework 15
- •Individual homeworks
- •Variant 1
- •Variant 2
- •Variant 3
- •Variant 4
- •Variant 5
- •Variant 6
- •Variant 7
- •Variant 8
- •Variant 9
- •Variant 10
- •Variant 11
- •Variant 12
- •Variant 13
- •Variant 14
- •Variant 15
- •Variant 16
- •Variant 17
- •Variant 18
- •Variant 19
- •Variant 20
- •Variant 21
- •Variant 22
- •Variant 23
- •Variant 24
- •Variant 25
- •Final exam trial tests (for self-checking)
- •Appendix
- •Values the functions and
- •List of the used books
- •Contents
Glossary
compatible events – совместные события; hypothesis – гипотеза
beforehand – заранее; to recognize – признавать, распознавать
a factory shop – цех завода; suitable detail – годная деталь
to overestimate – переоценить
Exercises for Seminar 5
5.1. There are 20 skiers, 6 bicyclists and 4 runners in a group of sportsmen. The probability to execute the corresponding qualifying norm is: for a skier – 0,9, for a bicyclist – 0,8, and for a runner – 0,75. Find the probability that a randomly chosen sportsman will execute the norm.
The answer: 0,86.
5.2. The first box contains 20 details and 15 of them are standard; the second – 30 details and 24 of them are standard; the third – 10 details and 6 of them are standard. Find the probability that a randomly extracted detail from a randomly taken box is standard.
The answer: 43/60.
5.3. There are radio lamps in two boxes. The first box contains 12 lamps, and 1 of them is non-standard; the second box contains 10 lamps, and 1 of them is non-standard. A lamp is randomly taken from the first box and placed in the second. Find the probability that a randomly extracted lamp from the second box will be non-standard.
The answer: 13/132.
5.4. At a deviation of an automatic device from the normal operating mode the signaling device C-1 acts with the probability 0,8, and the signaling device C-11 acts with the probability 1. The probabilities that the automatic device is supplied with C-1 or C-11 are equal to 0,6 and 0,4 respectively. A signal about cutting the automatic device has been received. What is more probable: the automatic device is supplied with the signaling device C-1 or C-11?
The answer: The probability that the automatic device is supplied with C-1, is equal to 6/11, and C-11 – 5/11.
5.5. The probability for products of a certain factory to satisfy the standard is equal to 0,96. A simplified system of checking on standardness gives positive result with the probability 0,98 for products satisfying the standard, and with the probability 0,05 – for products non-satisfying the standard. A randomly taken product has been recognized as standard at checking. Find the probability that it really satisfies the standard.
The answer: 0,998.
5.6. A digit is firstly randomly chosen from the digits {1, 2, 3, 4, 5}, and then the second digit – from the rest four digits. Find the probability that an odd digit will be chosen:
a) for the first time; b) for the second time; c) in both times.
The answer: a) 3/5; b) 3/5; c) 3/10.
5.7. Three cards are randomly selected without replacement from an ordinary deck of 52 playing cards. Compute the conditional probability that the first card selected is a spade, given that the second and third cards are spades.
The answer: 0,22.
5.8. Urn A contains 2 white balls and 1 black ball, whereas urn B contains 1white ball and 5 black balls. A ball is drawn at random from urn A and placed in urn B. A ball is then drawn from urn B. It happens to be white. What is the probability that the ball transferred was white?
The answer: 0,8.
