Probability Theory

Сhallenge 2

Here we are going to work with the distribution from the previous chapter!

Tarefa

Swipe to start coding

Please calculate the probability that your cat's weight will be unusual!

Import norm object.
Calculate the first one prob_1 that your cat's weight will be less than 2 kg with such parameters:
- Mean equals 4.2
- Standard deviation equals 1.
Calculate the second one prob_2 that the weight of your cat will be more than 11 kg with the parameters:
- Mean equals 4.2
- Standard deviation equals 1.
Calculate the probability that the weight of your cat will be more than 11 or less than 2 kg.

Compare it to the graph and the values of confidence intervals.

Solução

# Import norm object

from scipy.stats import norm

# Calculate the first probability

prob_1 = norm.cdf(x = 2, loc = 4.2, scale = 1)

# Calculate the second probability

prob_2 = norm.sf(x = 11, loc = 4.2, scale = 1)

# Calculate the whole probability

prob = prob_1 + prob_2

print("The probability is", prob)

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Seção 5. Capítulo 3

# Import norm object

from ___

# Calculate the first probability

prob_1 = ___(x = 2, loc = ___, scale = ___)

# Calculate the second probability

prob_2 = norm.___(x = ___, loc = ___, scale = ___)

# Calculate the whole probability

prob = ___

print("The probability is", prob)

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Probability Theory

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1. Learn Basic Rules

It's time to dive deeper into the probability theory. Here we will learn basic formulas. The main idea of the section is to help to understand the term probability using real-life examples.

Random Variable

Bernoulli Trial 1/2

Bernoulli Trial 2/2

Binomial Probability 1/2

Binomial probability 2/2

2. Probabilities of Several Events

Here, we will get acquainted with the rules in probability theory. This section will be more complicated than the previous one. It will be attractive because we are going to work with the real challenges. But it should be noted that we learn some formulas.

Add Probabilities

Calculate Connected Probabilities

Multiply probabilities

Dependent probabilities

Law of Total Probability

3. Conducting Fascinating Experiments

Doing experiments is always funny, but here we will combine exciting tasks with programming learning. In this section, we will work with the binom object to conduct experiments in Python.

The First Experiment

The Second Experiment

The Third Experiment

Combine Your Knowledge

4. Discrete Distributions

Distribution is a key to probability learning, but don't be petrified by this term. This section provides you with real-life explanations and relevant formulas.

Discrete Uniform Distribution

Calculate Fascinating Probability

Bernoulli Distribution

Binomial Distribution

Poisson Distribution

5. Normal Distribution

The normal distribution is the most commonly used one. Here we will work with the distribution with the help of real-life challenges.

Normal Distribution

Сhallenge 2