STAT4101 Schedule
PDF version available here.I do not expect any changes to the following schedule, but it should still be viewed as tentative. Perhaps class will be cancelled for snow, or a given topic will prove more difficult than anticipated. Any changes will be announced in class, by email (to your university email address) and posted on the website.
Homework for a given week is due by the end of class of Wednesday of the following week. For instance the homework for Week 1 (Sept. 5-7) is due on September 12.
Week 1: Sept. 5-7
What is Statistics (Chapter 1, and 2.1-2.2)
You should be able to . . .
- explain how statistical conclusions are made, and why probability models are necessary tools for making those conclusions.
- interpret relative frequency histograms and distributions.
- create and interpret sample means and standard deviations.
Week 2-3: Sept. 10-21
Probability (Chapter 2)
You should be able to . . .
- use set notation to describe an actual experiment and calculate sizes of various subsets.
- use the axioms of probability to calculate the probability of sets of events.
- use the multiplication rule, permutations, and combinations to count events and calculate probabilities.
- calculate conditional probabilities
- determine if events are independent or not
- calculate probabilites of intersections and unions of sets of events
- construct random variables from a set of events
Week 4-5: Sept. 24-Oct. 5
Discrete Random Variables (Chapter 3 - not 3.10)
You should be able to . . .
- compute expected values for a given probability distribution
- use the rules of expectation to compute expected values and variances of linear combinations.
- identify variables that are Binomial, Geometric, Negative Binomial, Hypergeometric, and Poisson, and compute probabilities and expected values for them.
- compute moment-generating function for a given probability distribution and use it to find the mean and variance.
- use moment-generating functions to find the probability distribution for a given variable.
- use Tchebysheff Ős theorem to find a bound on a desired probability.
Week 6a: Oct. 8-10
Exam (through Chapter 3)
- Monday will be a review; Wednesday is the exam.
Week 6b-8: Oct. 12-26
Continuous Random Variables (Chapter 4)
You should be able to . . .
- compute probabilities from both distribution functions and density functions.
- convert between distribution functions and density functions.
- compute expected values for a given probability distribution function.
- identify variables that are Uniform, Normal, Gamma, and Beta, and compute probabilities and expected values for them.
- compute moment-generating function for a given probability distribution and use it to find the mean and variance.
- use moment-generating functions to find the probability distribution for a given variable.
- use Tchebysheff Ős theorem to find a bound on a desired probability.
Week 9-11: Oct. 29-Nov. 16
Multivariate Distributions (Chapter 5 - not 5.9 or 5.10)
You should be able to . . .
- compute probabilities and expected values from joint probability distribution and density functions.
- convert between marginal, joint, and conditional distributions.
- identify whether or not two variables are independent from their joint distribution function.
- understand the relationship between uncorrelated and independent.
- use the rules of expectation to find means and variances of linear combinations of several variables, and of products of independent variables.
- find conditional expectations, both directly and by the rule of iterated expectations.
Week 12: Nov. 19-20
Midterm Exam (through Chapter 5)
- Monday will be a review; Tuesday is the exam.
- There will be no class on Wednesday, Nov. 21.
Week 13-15: Nov. 26-Dec. 12
Functions of Random Variables and the Central Limit Theorem (Chapters 6 & 7 -
not 6.6)
You should be able to . . .
- find the probability distribution of a function of random variables by using distribution func- tions, transformations, and moment-generating functions.
- be familiar with order statistics and able to perform basic operations using them.
- know how the chi squared, T, and F distributions are formed and be able to use their properties to find expected values and variances.
Week Final: December 17, 10:30-12:30 am
Final Exam (cumulative)