Data Science and Machine Learning (Theory and Projects) A to Z - Continuous Random Variables: Exponential Python

The video tutorial covers the exponential distribution, focusing on plotting its density function and exploring the impact of varying the Lambda parameter on the distribution's decay. It highlights that a larger Lambda results in a sharper decay, while a smaller Lambda leads to a smoother decay. The tutorial also clarifies that the density function's value can exceed one, as the area under the curve remains one. The video concludes with a preview of the Gaussian distribution, emphasizing its significance in probability theory and machine learning.

What is the primary characteristic of the X values in an exponential distribution?

• They can be negative.

• They must be positive or non-negative.

• They are always less than 1.

• They are always integers.

What error occurs when trying to loop over Lambda using a range with non-integer steps?

• Syntax error

• Type error

• Floor object cannot be interpreted as an integer

• Index out of range

How does a larger Lambda value affect the exponential distribution?

• It makes the decay smoother.

• It has no effect on the decay.

• It reverses the decay.

• It makes the decay sharper.

What happens to the exponential distribution when Lambda is decreased?

• The distribution becomes constant.

• The distribution becomes uniform.

• The decay becomes smoother.

• The decay becomes sharper.

What is true about the area under the curve of an exponential distribution?

• It varies with Lambda.

• It must always be equal to 1.

• It can be greater than 1.

• It is always less than 0.5.

Which of the following is not a property of the exponential distribution?

• The area under the curve is always 1.

• The decay rate is influenced by Lambda.

• The density function value can be greater than 1.

• The distribution is always symmetric.

What is the next topic to be discussed after the exponential distribution?

• Poisson distribution

• Binomial distribution

• Gaussian distribution

• Uniform distribution