Course Content
Probability Theory
Probability Theory
3. Conducting Fascinating Experiments
5. Normal Distribution
The First Experiment
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 codefrom scipy.stats import binom
. binom.pmf(k = 1000, n = 20000, p=0.20)
the probability of getting1000
successes amoung20 000
trials with the probability of success20%
.
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.
Task
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 fromscipy.stats
. - Calculate the probability that exactly
5
kittens out of12
will find a home with the probability of success75
%.
The output here is going to be less hopeful.
Task
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 fromscipy.stats
. - Calculate the probability that exactly
5
kittens out of12
will find a home with the probability of success75
%.
The output here is going to be less hopeful.
Everything was clear?
The First Experiment
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 codefrom scipy.stats import binom
. binom.pmf(k = 1000, n = 20000, p=0.20)
the probability of getting1000
successes amoung20 000
trials with the probability of success20%
.
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.
Task
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 fromscipy.stats
. - Calculate the probability that exactly
5
kittens out of12
will find a home with the probability of success75
%.
The output here is going to be less hopeful.
Task
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 fromscipy.stats
. - Calculate the probability that exactly
5
kittens out of12
will find a home with the probability of success75
%.
The output here is going to be less hopeful.
Everything was clear?
The First Experiment
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 codefrom scipy.stats import binom
. binom.pmf(k = 1000, n = 20000, p=0.20)
the probability of getting1000
successes amoung20 000
trials with the probability of success20%
.
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.
Task
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 fromscipy.stats
. - Calculate the probability that exactly
5
kittens out of12
will find a home with the probability of success75
%.
The output here is going to be less hopeful.
Task
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 fromscipy.stats
. - Calculate the probability that exactly
5
kittens out of12
will find a home with the probability of success75
%.
The output here is going to be less hopeful.
Everything was clear?
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 codefrom scipy.stats import binom
. binom.pmf(k = 1000, n = 20000, p=0.20)
the probability of getting1000
successes amoung20 000
trials with the probability of success20%
.
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.
Task
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 fromscipy.stats
. - Calculate the probability that exactly
5
kittens out of12
will find a home with the probability of success75
%.
The output here is going to be less hopeful.