Week | Topics |
---|---|
Week 1 | Basic Notions of Probability. Probability Space. Conditional Probability. |
Week 2 | Independent Events. Inclusion – Exclusion Principle. Bayes’ Theorem. |
Week 3 | Bernoulli’s Trials. Polynomial Trials. |
Week 4 | Random Variables: Introduction to Discrete Distributions. (Tutorial: Test I) |
Week 5 | Different Types of Continuous Distributions and Their Properties. |
Week 6 | Conditional Mathematical Expectation |
Week 7 | Joint Probability Distributions (Part 1: ) |
Week 8 | Midterm (March 13) |
Week 9 | Joint Probability Distributions (Part 2: ) |
Week 10 | Joint Probability Distributions (Part 3: Advanced Tasks) |
Week 11 | Joint Probability Distributions (Part 4: Normal Distribution) |
Week 12 | Characteristic Functions. Limit Theorems. (Tutorial: Test II) |
Week 13 | Maximum Likelihood Estimation. Parameter Estimation. |
Week 14 | Rao-Blackwell Theorem. Confidence Intervals. |
Item | Points | Comment |
---|---|---|
TA gratitude | 5 | depending on TA |
Tests (90 min.) | 10x2 | week 4 and week 12 |
Mid-term exam | 25 | week 8 |
Final exam | 45+5 | 45 – written, 5 – non-obligatory 'spoken' after written (week 16) |
Grade | Interval |
---|---|
A | 80+ |
B | 60-79 |
C | 40-59 |
Stepik page of this course
Set | Page | Tasks | Topic |
---|---|---|---|
2.2 | 42 | 10, 15, 18 | Events |
2.2 | 51 | 26, 31, 37, 44, 45 | Counting Sample Points |
2.5 | 59 | 52, 63, 72 | Additive Rules |
2.6 | 69 | 73, 91, 93, 94 | Conditional Probability and Product Rule |
2.7 | 76 | 99, 101 | Bayes' Rule |
~ | 77 | 104, 109, 113, 125 | Review Excercises |
See also:
Base rate fallacy [en/ru]
Prove that
(a) ;
(b) .
Let . Prove that . Is the opposite statement also true?
Let . Prove that . Is the opposite statement also true?
Prove that if , , then .
The letters of a word ``ITERATION'' are arranged in a random order. Find the probability that the same word has been obtained this way.
Let and be independent events. Prove that (a) and are independent; (b) and are independent.
Two players take turns flipping a coin. A player who gets heads first wins the game. What is the probability for the second player to win the game?
A fair die is rolled five times. What is the probability to get the same number at least three times in a row?
(a) A coin is flipped until the sequence ``tails, heads, tails'' is observed. What is the probability that the coin has been flipped exactly 7 times?
(b) A coin is flipped until the sequence ``tails, tails, tails'' is observed. What is the probability that the coin has been flipped exactly 7 times?
Four black balls and eight white balls are arranged into a line. Find the probability that
(a) the first white ball is situated in the third place;
(b) the last white ball is situated in the ninth place;
(с) the first black ball is situated in the third place and the last black ball is situated in the ninth place.
There are 10 white and 20 black balls in the first urn and 10 white balls and 10 black balls in the second urn. Four balls from the first urn and six balls from the second urn are selected at random and placed into the third urn (that was initially empty). Determine the probability that a ball randomly drawn from the third urn happens to be white.
There are 12 white balls and 8 black balls in the first urn; 8 white balls and 4 black balls in the second urn; 10 white balls in the third urn. 6 balls from the first urn, 5 balls from the second one, and 4 balls from the third one, all of them chosen at random, are transferred into the fourth urn that was empty at first. After that 2 arbitrary balls are simultaneously drawn from the fourth urn. Both of them have turned out to be white. Find the probability that these balls originate from different urns.
A message is transmitted via some communication channel. It can contain one of the three letter sequences: , , . On average, the last sequence is transmitted two times less often than the second one and three times less often than the first one. Due to interference a sequence can be distorted. The probability for a letter to be transmitted correctly is , whereas the probability that one letter turns into another one is . (Thus if is transmitted there is a probability to receive , probability to receive and probability to receive ). The distortions for each of the positions in the sequence do not depend on one another. Determine the probabilities that
(a) was transmitted, if has been received.
(b) was transmitted, if has been received.
A coin is flipped 10 times. What is the probability that there are exactly 7 heads and 3 tails?
Every projectile hits the target with probability 0.4. If the target was hit once, the probability to be destroyed is 0.3, twice – 0.7. If the target was hit 3 times or more it will be destroyed for sure. Find the probability that the target was destroyed if
On the average 2% of devices are broken. What is the probability that not less than 2 devices out of 6 are broken?
There are 10 devices. Every device independently breaks down with probability 0.15. Find the probability that:
(a) exactly 3 devices broke down
(b) exactly 3 devices broke down if it is known that at least 1 device broke down
A device is broken if at least five 1st-type-sensors or at least two 2nd-type-sensors are broken. From the set of all broken sensors there are 70% of type "1" and 30% of type "2" are broken (on the average). It is known that 5 sensors are broken.
(a) What combination of broken sensors is most likely?
(b) What is the probability that a device is broken?
The probability to hit an aim is . Find the probability that the second out of five shoots was failed if:
(a) the aim was hit exactly 3 times
(b) at least one shoot was failed
Nine persons entered a nine-floor house with an elevator. What is the probability that the elevator will stop on each floor. Every person can exit on each floor with the same probability.
Find the probability that in Bernoulli trials with three successes will happen earlier than five fails.
The first player rolls 6 dices and wins if "1" occurs at least once.
The second player rolls 12 dices and wins if "1" occurs at least twice.
Who has more chances to win?
A bar of length L is divided into three random parts. Determine the probability that a triangle may be formed from these parts.
Let
Plot the cumulative distribution function of .
a) Find
b) Find
c) Find
A coin is flipped times until two "tails" or two "heads" is observed.
Plot the cumulative distribution function of .
a) Find
b) Find
A random variable has three possible values: . It is known that and . Find , and .
Let
a) Find if it is known that .
b) Find if it is known that .
From a deck of cards (52 cards) randomly (without replacement) a card is taken until "ace of diamonds" is observed.
a) How many cards will be taken on average?
b) What is the probability that not more than 26 (a half) card will be taken?
Find a formula for for the uniform distribution.
Three students independently pass an exam with the probabilities , and . Let is a total number of students passed the exam.
Find and .
Ten people entered to an elevator of 9-floor house. How many times the elevator will stop on average?
A number from all three-digit numbers is picked randomly. Let is a number of different digits in our number. Find .
Find parameters of Binomial Distribution for a random variable or claim that is not from Binomial Distribution if:
a) and
b) and
For which a random variable has maximum dispersion?
A coin is flipped several times until 3 "tails" (so the first player wins) or 3 "heads) (so the second player wins) is observed (in total). Let is a number of times that coin was flipped. Find .
Let and . Find .
The probability to hit an aim is . Three misses are allowed.
a) Find the average number of shoots [before three misses].
b) Find the probability to shoot exactly eight times.
A fair dice is rolled until every number appears at least once. How many times (on the average) a fair dice will be rolled?
Inside a sphere of radius a point is picked randomly. Let is a distance from M to the sphere (to its surface).
Find , , and .
Let
a) Find so that is PDF for some distribution.
b) Find using found .
c) Find using found .
Let for .
a) Find so that is PDF for some distribution.
b) Find using found .
C) Find using found .
Let . Find:
a)
b)
c)
Let ( and are not given). It is known that and . Find , , and .
Let . Find .
Let .
Which event is more likely to happen: {} or {}?
Let ( is not given). It is known that .
Find .
Let . Find:
a) ;
b) ;
c) .
Let . It is known that . Find and .
Let . Find .
Prove that if then for
.
Prove that if then
.
Let and it is known that . What is maximum possible value of ?
Let . Prove that .
Note: Log-normal distribution
Let . So . Prove that PDF for is .
Average water consumption in a city is 50000 litres per day. Estimate the probability that real water consumption is less than tripple average.
Six fair dices are rolled. Let is the least digit occured on these six dices. Find .
fair dices are rolled. Let is the least digit occured on these dices. Find if .
Ten people entered to an elevator of 9-floor house. Let is a floor number on which the first person will exit. Find .
Ten people entered to an elevator of 9-floor house. Let is a floor number on which the last person will exit. Find .
A shooter has 25 bullets. The probability to hit a target is . The shooter shoots until the first miss or he is out of bullets.
Let a number of spent bullets.
Find .
Find if:
In a city there is sunny with the probability and it is cloudy with the probability . How many days on the average a person should be in the city to see both sunny and cloudy days?
A coin is flipped until "tails, tails" combination is observed.
How many times on average a coin will be flipped?
A fair dice is flipped until "66" is observed.
How many times on average a dice will be flipped
A fair dice is flipped until "666" is observed.
How many times on average a dice will be flipped?
A fair dice is flipped until "6" is observed.
Let is a sum of scores. Find .
Twelve people entered to an elevator of 12-floor house. How much people on average will be in the elevator after a certain person X exit the elevator.
Let , where and .
Prove that:
fair dices are rolled.
Let is a quantity of '6' appeared.
Let is a quantity of even numbers appeared.
Find (Correlation coefficient).
Let and are random variables with the joint distribution below.
Find .
Also find the law of distribution of , and .
\ | |||
---|---|---|---|
Ten people entered to an elevator of 9-floor house.
Let is a number of people exited at eighth floor.
Let is a number of people exited at ninth floor.
Find (Correlation coefficient).
Let a random variable from uniform distribution with possible values .
Let and .
Are and independent? Correlated?
Let , , and are some constants.
Prove that cov = cov.
A random vector has uniform distribution in
{}.
a) Find ;
b) Find .
Let and .
Are and dependent? Correlated?
Let a random vector with covariance matrix:
a) Find ;
b) Find .
Let and are independent.
Prove that .
Let and .
Let .
Find PDF .
Let and .
Let .
Find PDF .
Let and be independent exponentially distributed random variables with parameters and respectively. Let us consider random variables , . Determine whether and are independent. Is random variable independent from the event (i.e. from the indicator random variable of this event: )?
A marksman is shooting at a round target (centered at the origin). The vertical and horizontal coordinates of a point where the bullet hits the target are independent random variables. Determine the probability density of a random variable equal to the distance from point to the origin.
Let and be independent random variables with Cauchy distribution .
a) Prove that does not exist.
b) Prove that is also a Cauchy distributed random variable.
Let be independent exponentially distributed random variables, the parameter of the distribution being the same for all of them. Find the distribution for
a) ;
b) .
Let be a sequence of independent random variables uniformly distributed on , and , .
a) Find joint probability density of .
b) Find the correlation coefficient of and and show that it approaches 0 as .
The probability density of a random vector is given by
where is some number.
a) Find marginal distributions of and .
b) Find the correlation between and .
Let = ~ .
, .
a) Find (hint);
b) Find ;
c) Find ;
d) Find .
Let = ~ .
, .
a) Find ;
b) Find .
Let ~ – are independent.
Let and .
Find PDF of .
Let ~ and ~ are independent. Find .
Let ~ and ~ .
Prove that and are independent.
Let ~ and ~ with correlation coefficient equals to .
Find as a function of .
Let ~ and
~ .
{} and {} are independent samples.
Find PDF of:
a) ;
b) .
Let . Find .
Let is characteristic function of .
Find and .
Prove that a function is not a characteristic function.
Let and are independent.
Find PDF of using characteristic functions.
Let are all distributed as .
Let .
Find and .
Poisson limit theorem
De Moivre–Laplace theorem
De Moivre–Laplace theorem (integral case)
A book has 500 pages and 400 misprints. Let all misprints can occur independently on any page with equal probabilities. Estimate the probability that on the seventeenth page there will be more than one missprint.
The probability that there are no raisins in a bun is . Find the probability that in 1000 buns there are:
a) no buns without raisins
b) 3 buns without raisins
c) more than 2 buns without raisins
Every citizen independently votes for the candidate A with the probability equals and for the candidate B with the probability equals . There are 5000 citizens.
a) Estimate the probability that candidate A will have 1900 more votes than candidate B;
b) Estimate the probability that candidate A will have not less than 1900 more votes than candidate B.
(hint)
What is the minimum number of times a coin must be flipped to have 95% confidence that deviation of relative frequency of "tails" from the probability that "tails" occurs is not more than .
A fair dice is flipped 1000 times. With the probability we will have from to "six"-scores. Find the smallest [a,b] if:
a) ;
b) .
Note: such interval [a, b] is also called Confidence interval with the level of confidence equals to 95% (99%).
Let {} = {} – independent draws from a distribution. Find maximum likelihood estimation:
a) Poisson distribution. Parameter: ;
b) Exponential distribution. Parameter: ;
c) Normal distribution. Parameter: ;
d) Normal distribution. Parameter: .
Let {} = {} – independent draws from a distribution. Find sufficient statistics:
a) Uniform distribution . Parameter: ;
b) Poisson distribution. Parameter: ;
c) Normal distribution. Parameter: ;
d) Normal distribution. Parameter: .
Explain what is sufficient statistics. What is factorization criterion?
Let are independent random variables from the same distribution with PDF:
Using factorization criterion find sufficient two-dimensional statistics for parameter .
Let – is a sample from ( is not given).
Find bias of with variance less than .
Let – is a sample from .
Find 90%-confidence interval for
a) if sample mean is equal to and ;
b) if sample mean is equal to and adjusted sample variance is equal 4.
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