- •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 2
1. Two shooters make shots in a target. The probability of hit in the target at one shot by the first shooter is 0,7; and by the second shooter – 0,9. Find the probability that at one shot: a) both shooters will hit in the target; b) only one of the shooters will hit in the target.
2. Two automatic devices make plastic hangers. The probability of making a non-standard hanger by the first automatic device is 0,08; and by the second – 0,1. The productivity of the first automatic device is twice more than the second. Find the probability that a randomly taken detail will be non-standard.
3. The probability that a receipt written out by a shop assistant will be paid by a buyer is equal to 0,8. The shop assistant has written out 16 receipts. Find the most probable number of paid receipts and calculate its probability (receipt – чек).
4. Two independent random variables X and Y are given by the following tables of distribution:
X |
1 |
2 |
|
Y |
1 |
3 |
4 |
P |
0,7 |
0,3 |
|
P |
0,5 |
0,3 |
0,2 |
Compose the law of distribution of their sum Z = X + Y and check the property: D(X + Y) = D(X) + D(Y).
5. The random variable X is given by the distribution function:
Find: a) the mathematical expectation and the dispersion; b) the probability of hit of the random variable X into the interval (3; 8).
6. It is supposed that the strength of a let out party of a parachute fabric is a normally distributed random variable X with the mathematical expectation a = 200 kg/cm2 and the mean square deviation = 12 kg/cm2 (to let out – выпускать; parachute fabric – парашютная ткань).
Find: 1) the differential function of distribution f(x) and the integral function of distribution F(x); 2) the probability that X will take on a value from 175 up to 225 kg/cm2.
7. A factory makes products, and 80% of them are the first grade. Estimate the probability that the part of products of the first grade among 10000 made products will differ from the probability of making a product of the first grade no more than on 0,03 by absolute value.
8. There are the following data on lifetime of a separate parachute produced by a certain factory after studying 50 samples:
227 |
512 |
405 |
292 |
630 |
315 |
424 |
222 |
377 |
596 |
318 |
601 |
132 |
115 |
518 |
293 |
488 |
103 |
294 |
518 |
402 |
326 |
305 |
217 |
298 |
585 |
312 |
302 |
418 |
298 |
603 |
505 |
292 |
285 |
422 |
215 |
518 |
651 |
503 |
258 |
195 |
497 |
612 |
306 |
192 |
465 |
142 |
686 |
320 |
202 |
1) Compose the interval and the discrete variation series taking the beginning of the first interval equal 100, and the width of each interval equal 50.
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.
