- •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
Where a is the appearance of at least one of the events a1, a2, …, An; .
Partial case. If the events A1, A2, …, An have the same probability which is equal to p then the probability of appearance of at least one of these events:
P
(A)
= 1 – qn
where
A
is the appearance of at least one of the events A1,
A2,
…, An;
.
Example. The probabilities of hit in a target at shooting by three guns are the following: p1 = 0,8; p2 = 0,7; p3 = 0,9. Find the probability of at least one hit (the event A) at one shot by all three guns.
Solution: The probability of hit in the target by each of the guns doesn’t depend on results of shooting by other guns, therefore the considered events A1 (hit by the first gun), A2 (hit by the second gun) and A3 (hit by the third gun) are independent in union. The probabilities of events which are opposite to the events A1, A2 and A3 (i.e. the probabilities of misses) are equal respectively:
q1 = 1 – p1 = 1 – 0,8 = 0,2; q2 = 1 – p2 = 1 – 0,7 = 0,3;
q3 = 1 – p3 = 1 – 0,9 = 0,1.
The required probability P(A) = 1 – q1q2q3 = 1 – 0,2 0,3 0,1 = 0,994.
Example. There are 4 flat-printing machines at typography. For each machine the probability that it works at the present time is equal to 0,9. Find the probability that at least one machine works at the present time (the event A).
Solution: The events «a machine works» and «a machine doesn’t work» (at the present time) are opposite, therefore the sum of their probabilities is equal to 1: p + q = 1. Consequently, the probability that a machine doesn’t work at the present time is equal to q = 1 – p = 1 – 0,9 = 0,1.
The required probability P(A) = 1 – q4 = 1 – (0,1)4 = 0, 9999.
Example. A student looks for one formula necessary to him in three directories. The probability that the formula is contained in the first, second and third directories, is equal to 0,6; 0,7 and 0,8 respectively. Find the probability that the formula is contained:
a) only in one directory (the event A);
b) only in two directories (the event B);
c) in all the directories (the event C);
d) at least in one directory (the event D);
e) neither of the directories (the event E).
Solution: Consider elementary events and their probabilities:
А1
– the formula is in the first directory,
А2
– the formula is in the second directory,
А3
– the formula is in the third directory,
Express all the events A–E by the elementary events and their negations, and apply the above-stated theorems:
a)
b)
c)
d)
e)
Glossary
independent events – независимые события
mutual – взаимный; independent in union – независимые в совокупности
flat-printing machine – плоскопечатная машина
directory – справочник
Exercises for Seminar 4
4.1. The probability that a shooter hit in a target at one shot is equal to 0,9. The shooter has made 3 shots. Find the probability that all 3 shots will strike the target.
4.2. A coin and a die are tossed. Find the probability of joint appearance of the following events: «the coin lands on heads» and «the die lands on 6».
4.3. What is the probability that at tossing three dice 6 aces will appear at least on one of the dice (the event А)?
The answer: 0,722.
4.4. There are 8 standard details in a batch of 10 details. Find the probability that there is at least one standard detail among two randomly taken details.
4.5. Two dice are rolled. What is the conditional probability that at least one lands on 6 given that the dice land on different numbers?
4.6. The probability of hit in a target by the first shooter at one shot is equal to 0,8, and by the second shooter – 0,6. Find the probability that the target will be struck only with one shooter.
The answer: 0,44.
4.7. The probability to receive high dividends under shares at the first enterprise – 0,2; on the second – 0,35; on the third – 0,15. Determine the probability that a shareholder having shares of all the enterprises will receive high dividends:
a) only at one enterprise;
b) at least on one enterprise (a share – акция).
The answer: a) 0,4265; b) 0,564.
4.8. The first brigade has 6 tractors, and the second – 9. One tractor demands repair in each brigade. A tractor is chosen at random from each brigade. What is the probability that:
a) both chosen tractors are serviceable;
b) one of the chosen tractors demands repair (serviceable – исправный).
The answer: a) 20/27; b) 13/54.
