- •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 23
1. There are 11 green and 7 red balls in a box. Two balls are taken out at random. What is the probability that these balls will be the same color?
2. A warehouse has received a big batch of goods from two factories, and 70% of them have been delivered from the first factory. It is known that 75% goods from the first factory and 65% goods from the second have the higher grade. What is the probability that a randomly taken unit of goods in the warehouse has the higher grade?
3. The probability of hit in a target at one shot by a shooter is equal to 0,8. Determine the most probable number of hits in the target at 25 shots and calculate the probability of this number.
4. Two independent random variables are given by the following tables of distribution:
X |
–1 |
0 |
2 |
|
Y |
1 |
2 |
P |
0,4 |
0,3 |
0,3 |
|
P |
0,4 |
0,6 |
Compose the law of distribution of the random variable X Y and check the property: M(X Y) = M(X) M(Y).
5.
A random variable X
has the density of distribution
in the interval (0; 1), and f(x)
= 0 outside of the interval. Find:
a) the parameter C and the distribution function F(x);
b)
the probability that the following inequality holds:
.
6. The height of an adult man is a random variable distributed under a normal law with parameters: a = 175 cm, = 6 cm. Find the density of probability and the probability that the height of a randomly chosen man is in the interval from 170 up to 180 cm.
7. The dispersion of each of 4000 independent random variables does not exceed 16. Estimate the probability that the absolute value of the deviation of the arithmetic mean of these variables from the arithmetic mean of their mathematical expectations will not exceed 0,8.
8. The following data on lifetime (in hours) of a separate vacuum cleaner have been obtained at inspecting 100 vacuum cleaners of a given set:
548 |
956 |
521 |
1220 |
575 |
1121 |
1039 |
989 |
223 |
403 |
630 |
680 |
605 |
302 |
759 |
1158 |
335 |
985 |
556 |
1079 |
889 |
856 |
969 |
749 |
798 |
901 |
1133 |
1010 |
581 |
670 |
525 |
500 |
91 |
1205 |
1095 |
603 |
567 |
279 |
631 |
374 |
799 |
585 |
1209 |
887 |
268 |
735 |
267 |
833 |
960 |
332 |
967 |
650 |
86 |
264 |
807 |
159 |
78 |
573 |
1075 |
875 |
631 |
995 |
135 |
1158 |
432 |
580 |
370 |
930 |
479 |
1067 |
558 |
1095 |
985 |
841 |
897 |
940 |
901 |
376 |
570 |
970 |
196 |
470 |
609 |
890 |
469 |
889 |
373 |
459 |
1195 |
611 |
699 |
611 |
339 |
154 |
875 |
988 |
1169 |
531 |
957 |
551 |
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 200.
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.
