CS 7280

Topics in Statistics and Data Analysis

Spring 2016

MTh 11:45 - 1:25am, Ryder Hall 155

Instructor: Olga Vitek

Email: o.vitek@neu.edu

Office hours: WVH 310F, Mondays 1:30-2:30 or by appointment

Phone: (617) 373-6305

Mailbox: WVH 202

Teaching assistant: Ting Huang

Email: huang.tin@husky.neu.edu

Office hours: WVH 310C, Tuesdays 1-2pm.

Admin: Syllabus. Piazza, Blackboard.

R: CRAN, reference, search. RStudio.

Statistics texts: Kutner et al., 5th Ed., James et al, Faraway.

R texts:

Introduction

Mon, Jan 11: Notes. Reading: Donoho, 50 years of data science. Survey answers.

Basics of statistical inference. Intro to R.

Samples and populations. Hypothesis testing. A/B testing.

Introduction to R.

Thu, Jan 14: R notes. Reading: 1, 2 and 3. Examples: Sweave, Markdown, histograms. Hw1 out.

Mon, Jan 18: MLK day, no class, no office hours

Thu, Jan 21: Hw1 due. Hw2 out.

Mon, Jan 25: Current events: uncertainty, bias, uncertainty and bias.

Thu, Jan 28: Reading. Current events: 1 and 2. Hw2 due. Hw3 out.

Mon, Feb 1: Reading: Halsey et al., and discussion 1 and 2.

                    Reading: Rice derived distributions and two-sample comparison.

                    Current events: trade-off between Type I and Type II errors.

Thu, Feb 4: Guest lecture: Tsung-Heng Tsai and Robert Ness.

                    Fri, Feb 5: Hw3 due.

Linear regression

Estimation, testing, prediction. Multiple testing.

Categorical predictors. Multicollinearity. Selection of subset of predictors.

Mon, Feb 8: KNNL Ch.1-3. Hw4 out. Project guidelines.

Thu, Feb 11: No class

Mon, Feb 15: Presidents’ day, no class, no office hours

Thu, Feb 18: Project groups due. Hw4 due. Lecture notes. Hw5 out.

Mon, Feb 22: Summary of formulas.

Thu, Feb 25: Lecture notes. Hw5 due.

Mon, Feb 29: Lecture notes.

Thu, Mar 3: In-class midterm. Example of an old exam. Midterm solutions and grades.

Mon, Mar 7: Spring break, no class, no office hours

Thu, Mar 10: Spring break, no class

Mon, Mar 14: KNNL Ch.5-6 and 7-8.

Thu, Mar 17: Project proposal due. Hw6 out.

Mon, Mar 21: Lecture notes. KNNL Ch. 9-11.

Logistic regression

Logistic regression Mon, Mar 21:

Thu, Mar 24: Lecture notes. Example dataset and R. KNNL Ch.14. Hw6 due.

Mon, Mar 28: Hw7 out.

Thu, Mar 31:

Mon, Apr 4:

Weighted regression. Simulation-based inference

Permutations, bootstrap

Thu, Apr 7: Hw7 due. Lecture notes. KNNL Ch.11.

Basics of categorical data analysis

Basics of categorical data analysis.

Mon, Apr 11: Lecture notes.

Thu, Apr 14:

Fri, Apr 15: Project report due. Hw8 out.

Mon, Apr 18: Patriot’s day, no class, no office hours

Thu, Apr 21: Reading day, no class.

Fri, Apr 22: Project reviews due. Hw8 due.

Mon, Apr 25: Final exam 11:45am-1:25pm **** Ryder 143 ****. Practice exams 1 and 2. Grades.

Tentative schedule and handouts