- •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 17
1. A wardrobe mistress has given out simultaneously tickets to three persons given their coats in a wardrobe. After that she has mixed up all coats and hung up them at random. Find the probabilities of the following events: a) the wardrobe mistress will give out to each of three persons his own coat; b) only one person will receive its coat (wardrobe mistress – гардеробщица; to mix up – перепутать; to hang up – повесить что-либо; ticket – номерок).
2. Details from two automatic devices are delivered for an assemblage. It is known that the first automatic device gives 0,5 % of spoilage, and the second – 0,6 %. Find the probability that a randomly taken detail for an assemblage will be defective if 200 details have been delivered from the first automatic device, and 300 – from the second (assemblage – сборка).
3. 3 of 100 products on the average have a defect at a given technological process. Determine the probability that among randomly chosen 20000 products: a) exactly 562 products will be defective; b) from 545 up to 605 products will be defective.
4. Two independent random variables X and Y are given by the following tables of distribution:
X |
2 |
3 |
|
Y |
1 |
2 |
3 |
P |
0,7 |
0,3 |
|
P |
0,4 |
0,3 |
0,3 |
Compose the table of distribution of the random variable Z = X + Y and check the property: M(X + Y) = M(X) + M(Y).
5. A random variable X is given by the integral function:
Find: a) the differential function f(x); b) the mathematical expectation and the dispersion of X; c) the probability of hit of the random variable X into the interval (–1/2; 1/2).
6. The dispersion of a random variable distributed under a normal law is equal to 9 m, and the mathematical expectation is equal to 25 m. Find boundaries in which one should expect a value of the random variable with probability 0,9.
7. It has been established by checking the quality of produced electric bulbs that 97% of them have no less than a guaranteed lifetime (in hours). Estimate the probability that the part of bulbs (in a batch of 1000 electric bulbs) with the lifetime less than the guaranteed lifetime will differ from the probability of such an electric bulb no more than on 0,05.
8. At inspecting 60 fish packings of a given batch the following data on weight of a separate packing (in grammes) have been obtained:
248 |
239 |
263 |
242 |
279 |
246 |
265 |
242 |
263 |
255 |
273 |
249 |
209 |
252 |
266 |
278 |
247 |
248 |
202 |
252 |
259 |
235 |
249 |
264 |
246 |
275 |
274 |
296 |
232 |
217 |
292 |
294 |
223 |
265 |
267 |
258 |
213 |
277 |
275 |
266 |
248 |
286 |
268 |
288 |
232 |
262 |
244 |
246 |
252 |
259 |
258 |
254 |
231 |
251 |
229 |
258 |
267 |
249 |
253 |
249 |
1) Compose the interval and the discrete variation series taking the beginning of the first interval equal 200, 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.
