Course Calendar

Note: all lab responses are due 1 week after the lab is done in class.

[This is the schedule that we followed in 2012]

September 2012

8/31(F) Lab 1.1 Getting started: Matlab and Data Analysis/Stats basics

9/04(T) Lab 1.2 Variables, Functions, and Simple Plots

9/07(F) Lab 1.3 More plotting and (dot) m-files

9/11(T) *PS1.1 due. Lab 1.4 M-file Management; Differences in Cumulative Histograms

9/14(F) Lab 1.5 Did my drug really work? Statistical inference

9/21(F) Lab 1.6: What was the impact of my drug on average?

9/25(T) *PS1.2 due. Lab 1.7: Basic sample descriptors; tinkering with plots

9/28(F) Lab 1.8 How well did my drug do? Variance explained and discriminability

October 2012

10/02(T) Lab 2.1: Describing data with fits (models)

10/05(F) *PS1.3 due. Lab 2.2: Using fitting as a tool, not like a fool

10/12(F) Lab 2.3: Creating robust index values

10/16(T) No class / time to catch up / get ahead

10/19(F) Lab 2.4: Dealing with a truckload of data

10/23(T) *PS2.1 due. Lab 3.1: Time series: correlation, feature detection, rates

10/26(F) Lab 3.2: Frequency and Fourier analysis

10/30(T) Lab 3.3: Convolution and filtering

November 2012

11/02(F) *Team project 1 presentations

11/06(T) *TP1 write-up due. Lab 4.1 Basic image representations

11/09(F) *PS3.1 due. Lab 4.2: Digital image representations of the physical world

11/13(T) Lab 4.3: Image analysis: regions of interest

11/16(F) 4.4 Image analysis: functional imaging

11/20(T) *Team project 2 presentations

11/23(F) NO CLASS (Thanksgiving recess)

11/27(T) *TP2 write-up due. Work day. Catch up / work ahead.

11/30(F) *PS4.1, 5.1 High-dimensional space: data points as vectors

December 2012

12/04(T) 5.2 High-dimensional space: clustering and data dimensionality reduction

12/07(F) 5.3 High-dimensional space: interpolation; how principle component analysis works

12/11(T) Team project 3 presentations

12/19(Wed) **ALL MATERIAL DUE 5pm (Team 3 write-ups, any remaining labs to be turned in)**