Fall 2009

Math 3332 – Probability and Statistics

 

Date

Section

Assignment

Aug 17

Overview of descriptive statistics. Types of data. Introduction to Minitab. Plotting data. Ex. 14;

 

Read Chapter 1.

 

Aug 19

Measures of location and measures of variability. Boxplots.

Hw#1 due Aug 26: Chapter 1: ex. 20 (work the problem as told in the attached paper), 29 (is that a histogram that you have to draw??) 36, 64, 69. Note that the data can be downloaded from www.thomsonedu.com/statistics/devore. The syllabus has been updated with the link for installing Citrix. Also, the Resources link is now working.  

Aug 24

Sample space of an experiment and events. Axioms and properties of probability.

 

Aug 26

Permutations and combinations.

Read section 2.3.

Hw1 due.

Hw#2 due Sept 2: Chapter 2: 15, 19, 22, 34, 39, 49, 50, 74, 78, 83.

Aug 31

Conditional probability. Independence.

Read sections 2.4 and 2.5 (except for Bayes’ Theorem)

Sept 2

Bayes’ Theorem and applications.

Finish reading Chapter 2.

Quiz on 2.1-2.5; Hw#2 due.

Hw#3 due Sept 9: Ch2: 55, 59, 64, 67, 80, 84, 102.

More practice problems if you want: Ch2: 36, 38, 53, 60, 61, 62, 77, 79, 87, 97. 

Sept 3

Math Talks in CL 1003 at 12:30

 

Sept 9

Discrete Random Variables (Chapter 3). The cumulative distribution function.

Read 3.1-3.2.

Suggested practice problems: Ch3: 12, 13, 14, 18, 22, 23, 24.

Hw#4 due Sept 21: Ch 3: 13, 23, 32, 33, 39. More to come

Sept 14

Expected value of a random variable.

Read 3.3. (up to the variance of X).

More suggested problems: Ch 2(skip computation of variances) 29, 30, 32, 35, 36, 38.

Work the Practice for Exam 1 on Resources page.

Sept 16

Exam 1: through section 3.3 (only expected value)

You are allowed a formula sheet on the exam. Do not bring notes or hw problems or the answers to the Practice test.

Sept 17

 

Math Talks  at 12:30 in CL 1003: Title: Quest for Pi

Speaker: Dr. Lewis VanBrackle
Abstract:  In celebration of Anti-Pi Day (September 14, six months after and before Pi Day), we will take yet another look at estimating the value of pi.  Unlike my previous presentation on estimating pi, this somewhat lighthearted approach will include no “Buffonery.”  We will have some buffoonery, references to the Arthurian legend, Taylor’s series, and biased and asymptotically unbiased estimates.

Sept 21

Variance of a random variable. Introduction to the Binomial model.

Hw#4 due.

Sept 23

No class. We are still under water.

 

Sept 28

The Binomial Model. Computing probabilities. The mean and the variance of a binomial random variable. The hypergeometric distribution.

Read section 3.4. Do not use Binomial Tables. Use TI83 or Minitab instead. Read 3.5: The Hypergeometric distribution (no Negative Binomial).

Suggested problems: 48, 49, 50, 51, 52, 54, 55, 57, 58, 59, 60, 66; 69, 70.

Sept 30

The Hypergeometric distribution: applications and approximation. The Poisson distribution.

Quiz on 3.3-3.4

Hw#5 due Oct 7: Do the binomial plot as directed in the instructions; ex. 50, 59, 66, 74 (you do not have to write the entire distribution, just name it and give its parameters), 83, 87, 111, 113.

More suggested problems: 84, 88, 89, 100, 101, 102, 109, 110.

 

No Math Talks this Thursday

 

Oct 5

More on the Poisson distribution. Continuous random variables.

Read Chapter 4: section 4.1 and 4.2 through percentiles.

Suggested problems: section 4.1: ex. 1, 3, 5.

Brush up on Calculus: see the links for exponentials and logarithms and Professor’s Paul Dawkins at Lamar University review formulae on derivatives and integrals (on the Resources page).

Oct 7

Expected value and standard deviation for continuous distributions. The cumulative distribution function.

Hw#5 is due. Take home quiz is due.

Quiz in class on the Poisson and Binomial models.

Oct 11

The Exponential distribution. The Standard Normal model. 

Read 4.3 to Nonstandard normal distributions. Read 4.4 The exponential distribution (only).

Suggested problems: Ch 4: 4.2: 11, 12, 13, 14, 19, 22, 24

4.3: 28,

4.4: 60, 61, 62, 63, 69.

Supplementary ex: 100, 104, 106, 107, 108.

Check the Practice test #2 on the Resources page.

Oct 12

 

You are all invited to visit the Study Abroad fair in the Student Center University Rooms B, C, D & E between 10am-2pm. I am offering a Study abroad program to Romania with a three day stay in Paris next May.

Oct 13

More on the Normal model. Review problems for exam.

Homework #5 selected solutions are now posted on the resources page.

Oct 19

Exam #2 on Ch 3 and 4 through 4.4 (the exponential model only)

You may bring a formula sheet. No homework problems or practice test problems or solutions are allowed. You may bring a sheet with TI commands.

Oct 21

Joint probability distributions (Chapter 5).

Read 5.1 (only the discrete case) 5.2: expected value, covariance and correlation.

Suggested problems:5.1: 1, 2, 3, 5, 6, 22, 23, 30.

Oct 26

Expected values. Covariance and Correlation.

Hw#6 due Nov. 2nd;Chapter 5: 7, 13 (a,b), 26, compute Cov(X,Y) and correlation in ex 7, 38, 48, 54, 67.

Oct 28

Statistics and their distribution. The distribution of the sample mean. (5.2 -5.4)

Quiz on 5.1-5.2.

Nov 2nd

The Central Limit Theorem. The distribution of a linear combination of independent normal variables. The distribution of a sample proportion.

Read 5.4 and 5.5.

Suggested problems:61, 62, 64, 65, 67, 79, 80, 82, 84

Nov 4

More examples on Central Limit Theorem. Introduction to parameter estimation and Confidence intervals.

Hw#6 due on Nov.4. Additional problems: 64, 83.

Read 6.1 through Example 6.7.

Since you asked for it, here is a Take home quiz for you.

Nov 9

Large sample confidence intervals for means.

 

Nov 11

Confidence intervals for proportions. Small sample confidence intervals.

Read 7.1-7.3. (skip one-sided confidence intervals, bootstrap, prediction and tolerance)

Hw#7: due Nov 23: Chapter 7: 5 (a,c,d), 12, 16, 25; 30(a,b), 32, 33, 47 (in part a just construct a 95% confidence interval for the true mean).  

Nov 16

 

 

Nov 18

Exam #3 on Ch. 5 (what has been covered), 7.