Зміст курсу

Теорія ймовірностей

1. Ознайомемося з основними правилами

Випадкова змінна Схема Бернуллі 1/2 Схема Бернуллі 2/2 Біноміальна ймовірність 1/2 Біноміальна ймовірність 2/2

2. Ймовірності декількох подій

Додавання ймовірностей Обчислення зв'язаних ймовірностей Виклик Перемножуємо ймовірності Залежні ймовірності Закон повної ймовірності Теорема Байєса Виклик

3. Проводимо захоплюючі експерименти

Перший експеримент Другий експеримент Третій експеримент Поєднуйте свої знання

4. Дискретні розподіли

Дискретний рівномірний розподіл Обчислити захоплюючу ймовірність Розподіл Бернуллі Біноміальний розподіл Виклик Пуассонівський розподіл Виклик

5. Нормальний розподіл

Нормальний розподіл Виклик 1 Виклик 2

Перший експеримент

To be a data analyst, it is crucial to understand that we are going to conduct a lot of experiments. Here, we are going to get acquainted with several gripping functions!

Real-life example:

Imagine that we are working for a real estate agency, and we need to know how many positive answers we will get from all interviewees.

In this course, we will learn such interesting functions programming-wise.

Look at the example and everything will be clear:

General formula:

In this experiment, we will work with the binom.pmf(k, n, p) function. This function helps calculate the probability of receiving exactly k successes among n trials with the probability of success for each experiment p.

Explanation:

As usual, we are importing objects from scipy.stats with this code from scipy.stats import binom.
binom.pmf(k = 1000, n = 20000, p=0.20) the probability of getting 1000 successes amoung 20 000 trials with the probability of success 20%.

Interesting fact:

The result of our code is zero, but we worked with an enormous sample; in the task, we will receive a more understandable result.

Завдання

Imagine that our task is to do some calculations for a charity organization just for practice.

Your task here is to calculate the probability that exactly 5 kittens will find a home; there are 12 kittens in the shelter. In this city, kittens are taken from a shelter with a probability of 75%. Import relevant library to do it.

Import binom object from scipy.stats.
Calculate the probability that exactly 5 kittens out of 12 will find a home with the probability of success 75%.

The output here is going to be less hopeful.

Завдання

Imagine that our task is to do some calculations for a charity organization just for practice.

Import binom object from scipy.stats.
Calculate the probability that exactly 5 kittens out of 12 will find a home with the probability of success 75%.

The output here is going to be less hopeful.

Все було зрозуміло?

Секція 3. Розділ 1

Перший експеримент

To be a data analyst, it is crucial to understand that we are going to conduct a lot of experiments. Here, we are going to get acquainted with several gripping functions!

Real-life example:

Imagine that we are working for a real estate agency, and we need to know how many positive answers we will get from all interviewees.

In this course, we will learn such interesting functions programming-wise.

Look at the example and everything will be clear:

General formula:

Explanation:

As usual, we are importing objects from scipy.stats with this code from scipy.stats import binom.
binom.pmf(k = 1000, n = 20000, p=0.20) the probability of getting 1000 successes amoung 20 000 trials with the probability of success 20%.

Interesting fact:

The result of our code is zero, but we worked with an enormous sample; in the task, we will receive a more understandable result.

Завдання

Imagine that our task is to do some calculations for a charity organization just for practice.

Import binom object from scipy.stats.
Calculate the probability that exactly 5 kittens out of 12 will find a home with the probability of success 75%.

The output here is going to be less hopeful.

Завдання

Imagine that our task is to do some calculations for a charity organization just for practice.

Import binom object from scipy.stats.
Calculate the probability that exactly 5 kittens out of 12 will find a home with the probability of success 75%.

The output here is going to be less hopeful.

Все було зрозуміло?

Секція 3. Розділ 1

Перший експеримент

To be a data analyst, it is crucial to understand that we are going to conduct a lot of experiments. Here, we are going to get acquainted with several gripping functions!

Real-life example:

Imagine that we are working for a real estate agency, and we need to know how many positive answers we will get from all interviewees.

In this course, we will learn such interesting functions programming-wise.

Look at the example and everything will be clear:

General formula:

Explanation:

As usual, we are importing objects from scipy.stats with this code from scipy.stats import binom.
binom.pmf(k = 1000, n = 20000, p=0.20) the probability of getting 1000 successes amoung 20 000 trials with the probability of success 20%.

Interesting fact:

The result of our code is zero, but we worked with an enormous sample; in the task, we will receive a more understandable result.

Завдання

Imagine that our task is to do some calculations for a charity organization just for practice.

Import binom object from scipy.stats.
Calculate the probability that exactly 5 kittens out of 12 will find a home with the probability of success 75%.

The output here is going to be less hopeful.

Завдання

Imagine that our task is to do some calculations for a charity organization just for practice.

Import binom object from scipy.stats.
Calculate the probability that exactly 5 kittens out of 12 will find a home with the probability of success 75%.

The output here is going to be less hopeful.

Все було зрозуміло?

To be a data analyst, it is crucial to understand that we are going to conduct a lot of experiments. Here, we are going to get acquainted with several gripping functions!

Real-life example:

Imagine that we are working for a real estate agency, and we need to know how many positive answers we will get from all interviewees.

In this course, we will learn such interesting functions programming-wise.

Look at the example and everything will be clear:

General formula:

Explanation:

As usual, we are importing objects from scipy.stats with this code from scipy.stats import binom.
binom.pmf(k = 1000, n = 20000, p=0.20) the probability of getting 1000 successes amoung 20 000 trials with the probability of success 20%.

Interesting fact:

The result of our code is zero, but we worked with an enormous sample; in the task, we will receive a more understandable result.

Завдання

Imagine that our task is to do some calculations for a charity organization just for practice.

Import binom object from scipy.stats.
Calculate the probability that exactly 5 kittens out of 12 will find a home with the probability of success 75%.

The output here is going to be less hopeful.

Секція 3. Розділ 1

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів