SOCR EduMaterials FunctorActivities Bernoulli Distributions

From Socr

(Difference between revisions)
Jump to: navigation, search
Line 11: Line 11:
Below you can see a snapshot of the MGF of the distribution of <math> X \sim Bernoulli(0.8) </math>
Below you can see a snapshot of the MGF of the distribution of <math> X \sim Bernoulli(0.8) </math>
<center>[[Image:BernoulliMGF.jpg|600px]]</center>
<center>[[Image:BernoulliMGF.jpg|600px]]</center>
-
 
Do you notice any similarities between the graphs of these MGF's between any of these distributions?
Do you notice any similarities between the graphs of these MGF's between any of these distributions?
 +
 +
* '''Exercise 2:''' Use SOCR to graph and print the MGF of the distribution of a geometric random variable with <math> p=0.2,  p=0.7 </math>.  What is the shape of this function?  What happens when <math> p </math> is large?  What happens when <math> p </math> is small?
 +
 +
* '''Exercise 3:''' You learned in class about the properties of MGF's If <math> X_1, ...X_n are iid. and Y = \sum_{i=1}^n X_i. </math> then

Revision as of 02:38, 9 January 2008

This is an activity to explore the Moment Generating Functions for the Bernoulli, Binomial, Geometric and Negative-Binomial Distributions.

  • Exercise 1: Use SOCR to graph the MGF's and print the following distributions and answer the questions below. Also, comment on the shape of each one of these distributions:
    • a. X \sim Bernoulli(0.5)
    • b. X \sim Binomial(1,0.5)
    • c. X \sim Geometric(0.5)
    • d. X \sim NegativeBinomial(1, 0.5)

Below you can see a snapshot of the MGF of the distribution of  X \sim Bernoulli(0.8)

Do you notice any similarities between the graphs of these MGF's between any of these distributions?

  • Exercise 2: Use SOCR to graph and print the MGF of the distribution of a geometric random variable with p = 0.2,p = 0.7. What is the shape of this function? What happens when p is large? What happens when p is small?
  • Exercise 3: You learned in class about the properties of MGF's If  X_1, ...X_n are iid. and Y = \sum_{i=1}^n X_i. then
Personal tools