Data Science and Machine Learning (Theory and Projects) A to Z - Experiment: Random Experiment

The video tutorial explains the concept of experiments in probability, focusing on the unpredictability of outcomes. It uses examples like tossing a fair coin and rolling a four-sided die to illustrate randomness. The tutorial emphasizes that experiments can have multiple outcomes, which are not predictable with certainty, hence termed as random experiments. It also discusses the interchangeability of terms like 'random experiment' and 'random trial'.

What is the primary characteristic of an experiment as described in the video?

• It is a process with a single possible outcome.

• It always produces the same outcome.

• It is a process that is always predictable.

• It is a process that can produce multiple outcomes.

Why is a coin toss considered a random experiment?

• Because the outcome is unpredictable.

• Because it always lands on heads.

• Because it involves a complex process.

• Because it requires special equipment.

What does the repetition of a coin toss under the same conditions demonstrate?

• The predictability of experiments.

• The randomness of results.

• The need for different conditions.

• The certainty of outcomes.

What is the result of rolling a four-sided die?

• A number that depends on the previous roll.

• Always the number 4.

• A random number between 1 and 4.

• A predictable number.

How does rolling a die illustrate the concept of a random experiment?

• It always results in the same number.

• The outcome is known before rolling.

• The result is unpredictable each time.

• It requires a specific technique.

What is the outcome of combining a coin toss with a die roll?

• A result that is not random.

• Always a head and a four.

• A combination of outcomes from both.

• A single predictable result.

What term can be used interchangeably with 'random experiment'?

• Random trial

• Random process

• Random certainty

• Random outcome