Fall 2011
Tuesday & Thursday. 2:10–3:30. Town 0206
Heike Hofmann, hofmann@iastate.edu.
Office hours: TBD
Susan Vanderplas, srvanderplas+stat430@gmail.com.
Office hour: Fridays 12-1 in 1414 Snedecor
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Course syllabus describing objectives, modules and assessment.
| Date | Lecture Notes | Homework and Resources | |
|---|---|---|---|
| Probability & Distributions | |||
| Aug 23 | Sample Spaces, Kolmogorov Axioms, Counting | HW #1, due Aug 30 | |
| Aug 25 | Conditional Probability, Independence, Bayes Rule, see also Ewens & Grant, p. 3-6, 36-41 or Baron p. | ||
| Aug 30 | Bayes, Discrete Random Variables, Expectation, see Ewens & Grant, p. 6,7, 13-16; Baron p. | HW #2, due Sep 6 | |
| Sep 1 | Moment generating function, discrete distributions, see Ewens & Grant, p. 7-19 | ||
| Sep 6 | Joint discrete distributions, intro to continuous distributions, see Ewens & Grant, p. 55-57, 24, 28, 42 | HW #3, due Sep 13 | |
| Sep 8 | Continuous random variables and special distributions | ||
| Sep 13 | Central Limit Theorem and Corollaries, Relationship: Poisson and Gamma, Multivariate random variables, convolution see Ewens & Grant, p. 59-60, 75-76, 133. | HW #4, due Sep 20 | |
| Basic Simulations | |||
| Sep 15 | Intro to Random Number Generators, R code | ||
| Sep 20 | Review of material using Simulations., R code | Review material for exam. previous exam. focus on questions 3 and 4. | |
| Statistical Inference | |||
| Sep 22 | Midterm Exam (2:10 - 3:00). Intro to Statistics: graphical summaries and estimation |
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| Sep 27 | Review of exam, Graphical summaries and estimation. | ||
| Sep 29 | Parameter Estimation, Intro to Confidence Intervals | Project I, due dates Nov 3/Nov 8 (midnight). | |
| Oct 4 | Confidence Intervals: large and small samples | HW #5, due Oct 11 | |
| Oct 6 | Intro to R, R code, R reference card | ||
| Statistical Models | |||
| Oct 11 | Hypothesis testing, R code, data | HW #6, due Oct 18 | |
| Oct 13 | Intro to Linear Models: Regression and Anova | ||
| Oct 18 | Normal Model, Residuals and Prediction in Linear Models, Model Comparisons, R code | ||
| Oct 20 | General Linear Models in R, R code | ||
| Oct 25 | Midterm Exam II, Logistic Regression | HW #7, due Nov 1, cheese data , mystery | |
| Oct 27 | Logistic Regression | R code | |
| Nov 1 | Trees and Random Forests in R, R code | no homework this week - focus on project submission | |
| Specialized Topics of interest | |||
| Advanced Simulations | |||
| Nov 3 | More Theoretical look on Trees and Random Forests, , R code | ||
| Nov 8 | Bootstrapping, Intro to Markov Chains | HW #8, due Nov 15, Final Project, due dates Nov 15, Nov 29, Dec 6 | |
| Nov 10 | Markov Chains | ||
| Nov 15 | Hidden Markov Models, R code | ||
| Nov 17 | Metropolis Hastings, Gibbs Sampling, R code | ||
| Nov 22/24 | Thanksgiving Break | ||
| Nov 29 | Clustering Methods, R code | ||
| Dec 1 | Clustering, Project Discussion | ||
| Final Projects and Exam | |||
| Presentations Tuesday, December 6, 2:10 - 2:30 | |||
| Date | Presenter | Title | |
|---|---|---|---|
| 2:10 - 2:35 | Jennifer Chang, Liu Jie, Kejue Jia, Ruolin Liu | Diabeties | |
| 2:35 - 3:00 | Sudhanshu Vyas, Chetan Govindaiah, Kyoung Cho, Nicholas Booher | Identification of Fault Critical Areas in FPGAs | |
| 3:00 - 3:25 | Jinsheng Zhang, Jingwei Yang, Mei Li, Zhang Zhang, Haihua Xie | Evaluation of Quality of Wines | |
| Presentations Thursday, Dec 8, 2:10 - 3:30 | |||
| Date | Presenter | Title | |
|---|---|---|---|
| 2:10 - 2:35 | Katherine Wilkins, Benjamin Mulaosmanovic, Kannan Sankar | Prediction of Breast Tumor Malignancy in Inconclusive Samples Using Logistic Regression | |
| 2:35 - 3:00 | Marisol Martinez-Escobar, Chad Nelson, Kuan Wu | Tumor segmentation | |
| 3:00 - 3:25 | Nate Bowerman, Jenny Woody, Michael Svendsen, Sylvia Do | Predicting Upcoming Wins in the NHL | |