Learn The First Experiment | Conducting Fascinating Experiments

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.


              1234
            
from scipy.stats import binom
# Calculate the probability
experiment = binom.pmf(k = 1000, n = 20000, p=0.20)
print(experiment)

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.

Task

Swipe to start coding

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.

Solution

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Section 3. Chapter 1

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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:


              1234
            
from scipy.stats import binom
# Calculate the probability
experiment = binom.pmf(k = 1000, n = 20000, p=0.20)
print(experiment)

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.

Task

Swipe to start coding

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.

Solution

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 3. Chapter 1

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The First Experiment

Solution

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The First Experiment

Solution

Awesome!