Chapter 6 Probability Density Functions

Question 1

What is a probability density function (PDF)?

Answer 1

Is the derivative of a cumulative destribution function (CDF)

Question 2

What is the units associated with computing the density at a location along a PDF?

Answer 2

units of probability mass per x

Question 3

What is a kernal density estimation (KDE)?

Answer 3

algorithm that takes a sample and finds an appropriately smooth pdf that fits the data.

Question 4

What are the three benefits for estimating a density function with a KDE?

Answer 4

Visualization

Interpolation

Simulation

Question 5

What is a statistic?

Answer 5

a number that represents a sample (multiple values)

Question 6

What is Skewness?

Answer 6

property that describes the shape of a distribution

Question 7

Mathmatical definition of central moments?

Answer 7

Question 8

What is the mathmatical definition of Pearson’s median skewness coeffcient?

Answer 8

Question 9

What is the mathmatical definition of the PDF for a normal distribution.

Answer 9