- •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 20
1. The probability of hit in a target by the first shooter is 0,8, and by the second shooter – 0,7. The shooters have shot simultaneously. What is the probability that only one of them hit in the target?
2. 1100 of 2000 tubes belong to the first batch, 650 – to the second, and 250 – to the third. 7% of the first batch, 6% of the second and 8% of the third are defective tubes. One tube is chosen at random. Determine the probability that the chosen tube is defective.
3. It has been established by long observations that 14 days at April are on the average rainy in Chicago. What is the probability that 5 of 7 randomly chosen days of the month will be rainy?
4. Let X be a discrete random variable distributed under the following law:
-
X
0
1
2
3
4
5
р
0,14
0,18
0,06
0,3
0,04
0,28
Find: a) the mathematical expectation and the dispersion of the random variable X; b) the probability of the following event: 1 < X 3.
5. A random variable X is given by the density of distribution f(x) = A(3x – x2) in the interval (0; 2), and f(x) = 0 outside of the interval. Find:
а) parameter A;
b) the mathematical expectation and the dispersion of the variable X.
6. A detail made by an automatic device is recognized suitable if the deviation of its controllable weight from the design one does not exceed 15 g. Random deviations of the controllable weight from the design one are subordinated to a normal law with dispersion 16 and mathematical expectation 20 g. How many percents of suitable details does the automatic device produce?
7. Estimate the probability that the absolute value of the deviation of the average height of 500 persons from the mathematical expectation of a random variable expressing the height of each person will not exceed 1 cm, assuming that the dispersion of each of these random variables does not exceed 7.
8. The following data on strength of a metal cable of a given batch have been received after testing 60 samples:
709 |
707 |
738 |
735 |
726 |
738 |
702 |
734 |
774 |
785 |
761 |
787 |
757 |
769 |
728 |
755 |
736 |
749 |
725 |
736 |
768 |
759 |
736 |
782 |
716 |
766 |
741 |
752 |
754 |
753 |
774 |
777 |
713 |
759 |
753 |
743 |
746 |
761 |
765 |
755 |
771 |
732 |
748 |
766 |
759 |
739 |
749 |
751 |
731 |
768 |
713 |
717 |
752 |
795 |
792 |
751 |
765 |
746 |
775 |
773 |
1) Compose the interval and the discrete variation series taking the beginning of the first interval equal 700, 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.
