Data Science and Machine Learning (Theory and Projects) A to Z - Random Variables: Geometric Random Variable Python Prac

The video tutorial introduces geometric random variables in Python, explaining how to define a function for geometric trials. It covers generating and analyzing data, plotting results using histograms, and exploring the impact of probability on distribution. Advanced visualization techniques are demonstrated, and the session concludes with a preview of binomial random variables.

What is the primary focus of the initial section of the video?

• Discussing Python syntax

• Defining a function for geometric random variables

• Correcting spelling errors in code

• Explaining the concept of Bernoulli trials

What does a geometric random variable represent?

• The number of trials until the first success

• The average number of successes

• The probability of success in a single trial

• The number of successes in a fixed number of trials

Which loop is used to simulate trials in the geometric random variable function?

• For loop

• Do-while loop

• While loop

• If-else loop

What happens to the geometric random variable values when the probability of success is reduced?

• They become more frequent

• They become less frequent

• They remain unchanged

• They increase in number

What is the purpose of generating 1000 geometric trials in the video?

• To test the function's efficiency

• To observe the distribution of results

• To find the average number of trials

• To compare with binomial trials

How does the distribution of trials change with a higher probability of success?

• The distribution becomes wider

• The distribution becomes narrower

• The distribution becomes random

• The distribution remains the same

What visualization techniques are used to display the distribution of geometric random variables?

• Box plots and area charts

• Line graphs and pie charts

• Bar charts and scatter plots

• Histograms and density plots

What is the effect of decreasing the probability of success on the distribution's peak?

• The peak disappears

• The peak remains unchanged

• The peak becomes higher

• The peak becomes lower

What is one method mentioned for estimating probability distributions from data?

• Using pie charts

• Using line graphs

• Using histograms

• Using scatter plots

What topic is introduced at the end of the video?

• Poisson random variables

• Normal distribution

• Binomial random variables

• Uniform distribution