- •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
Variant 10
1. Three dice are tossed. Find the probability that the sum of landed aces of the dice is divided on 5.
2. A collector has received 4 boxes of details made by the first factory, and 3 boxes of details made by the second factory. The probability that a detail of the first factory is standard is equal to 0,75; the second factory – 0,85. Find the probability that a randomly extracted detail from a randomly chosen box will be standard (collector – сборщик).
3. There is a group of 60 persons born at April. Find the probability that the birthday for three persons will be the first of April. Assume that the probability of a birth in a fixed day of April is equal to 1/30.
4. The probability that a book necessary for a student is available in a library is equal to 0,4. Compose the law of distribution of the number of libraries which will be visited by the student if there are five libraries in the city.
5. The distribution function of a continuous random variable X is given by:
Find: 1) the density of distribution; 2) the mathematical expectation and the dispersion of X; 3) the probability of hit of the random variable X into the interval (0; /8).
6. A random variable X is normally distributed with mathematical expectation M(X) = 12 and dispersion D(X) = 4. Find the probability that:
а) X will take on a value belonging to the interval (7; 14);
b) X will differ from the mathematical expectation less than on 1,5.
7. The dispersion of each of 1000 independent random variables does not exceed 4. Estimate the probability that the arithmetic mean of these random variables will differ from the arithmetic mean of their mathematical expectations less than on 0,15.
8. There are the following data on monthly volume of cigarettes (in thousand packs) of 100 supermarkets:
32 |
87 |
52 |
61 |
52 |
64 |
79 |
67 |
58 |
46 |
58 |
53 |
83 |
31 |
56 |
50 |
65 |
47 |
58 |
77 |
53 |
47 |
51 |
70 |
40 |
54 |
53 |
26 |
13 |
55 |
6 |
86 |
73 |
56 |
1 |
69 |
62 |
39 |
49 |
77 |
48 |
66 |
53 |
51 |
78 |
66 |
52 |
63 |
53 |
88 |
68 |
16 |
31 |
74 |
45 |
49 |
66 |
80 |
95 |
93 |
69 |
14 |
56 |
41 |
76 |
60 |
42 |
51 |
49 |
74 |
28 |
45 |
62 |
55 |
43 |
51 |
54 |
66 |
67 |
63 |
68 |
52 |
48 |
72 |
34 |
40 |
64 |
17 |
56 |
69 |
21 |
25 |
35 |
37 |
54 |
33 |
45 |
37 |
45 |
28 |
1) Compose the interval and the discrete variation series taking the beginning of the first interval equal 0, and the width of each interval equal 10.
2) Construct the histogram and the polygon of relative frequencies of distribution.
3) Find the mode and the median (using the discrete series).
4) Find empirical functions of distribution of continuous and discrete variation series; and construct their graphs.
