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.
1234from 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.statswith this codefrom scipy.stats import binom. binom.pmf(k = 1000, n = 20000, p=0.20)the probability of getting1000successes amoung20 000trials 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.
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
binomobject fromscipy.stats. - Calculate the probability that exactly
5kittens out of12will find a home with the probability of success75%.
The output here is going to be less hopeful.
Solución
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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:
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.
1234from 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.statswith this codefrom scipy.stats import binom. binom.pmf(k = 1000, n = 20000, p=0.20)the probability of getting1000successes amoung20 000trials 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.
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
binomobject fromscipy.stats. - Calculate the probability that exactly
5kittens out of12will find a home with the probability of success75%.
The output here is going to be less hopeful.
Solución
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones¡Gracias por tus comentarios!
Awesome!
Completion rate improved to 3.7single
