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Probability Theory

Binomial Probability 1/2

Think about the Bernoulli trial. We have experimented with five coins, but only once. As we want to work with data, it is crucial we understand experimenting once can be a little bit irrational; maybe we were tossing a coin on the street, and the wind became an obstacle, so it is essentially important to have several tries.

As you remember the definition for the Bernoulli trial it is time to move on to Binomial probability.

It is when we have a defined number of successful trials among all attempts in an experiment with two outcomes.

Example:

Tossing five coins three times. Event "Tossing a coin" has only two outcomes: head or tail.

question-icon

Match the example of probability with the Bernoulli Trial or Binominal Probability.

A test with 12 questions where each one has two possible variants: "yes" or "not".
Pulling the card of the deck, where nine of the heart is a success, and other outcomes are a failure.
Rolling a dice eight times where number 3 is a success, and other outcomes are a failure.

Click or drag`n`drop items and fill in the blanks

Everything was clear?

Section 1. Chapter 4
course content

Course Content

Probability Theory

Probability Theory

1. Learn Basic Rules

Random VariableBernoulli Trial 1/2Bernoulli Trial 2/2Binomial Probability 1/2Binomial probability 2/2

2. Probabilities of Several Events

Add ProbabilitiesCalculate Connected ProbabilitiesChallengeMultiply probabilitiesDependent probabilitiesLaw of Total ProbabilityBayes Theorem Challenge

3. Conducting Fascinating Experiments

The First ExperimentThe Second ExperimentThe Third ExperimentCombine Your Knowledge

4. Discrete Distributions

Discrete Uniform DistributionCalculate Fascinating ProbabilityBernoulli DistributionBinomial DistributionChallengePoisson DistributionChallenge

5. Normal Distribution

Normal DistributionChallenge 1Сhallenge 2

Binomial Probability 1/2

Think about the Bernoulli trial. We have experimented with five coins, but only once. As we want to work with data, it is crucial we understand experimenting once can be a little bit irrational; maybe we were tossing a coin on the street, and the wind became an obstacle, so it is essentially important to have several tries.

As you remember the definition for the Bernoulli trial it is time to move on to Binomial probability.

It is when we have a defined number of successful trials among all attempts in an experiment with two outcomes.

Example:

Tossing five coins three times. Event "Tossing a coin" has only two outcomes: head or tail.

question-icon

Match the example of probability with the Bernoulli Trial or Binominal Probability.

A test with 12 questions where each one has two possible variants: "yes" or "not".
Pulling the card of the deck, where nine of the heart is a success, and other outcomes are a failure.
Rolling a dice eight times where number 3 is a success, and other outcomes are a failure.

Click or drag`n`drop items and fill in the blanks

Everything was clear?

Section 1. Chapter 4
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