Class Schedule

This page contains information about class activities. The schedule for the current week is at the top; scroll down to review the schedule for other weeks, or use the following quick links.

Week: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14

Week Fourteen

Monday, May 7th (Note: bring computers to class)

• Topics: Principal Component Regression
• Read:
  • Chemometrics: 292-297
• Handouts:
  • Take-home Final Exam
• Homework:
  • None

Wednesday, May 9th

• Topics:
  • Review
• Read:
  • None
• Handouts:
  • None
• Homework:
  • None

Week Thirteen

Monday, April 30th (Note: bring computers to class)

• Topics:
  • Cluster Analysis
  • Matrix Math
• Read:
  • Chemometrics: 224-230, 409-412
• Handouts:
  • Using R for an Hierarchial Cluster Analysis
  • Working With Matricies in R
• Homework:
  • Second Journal Article Review

Wednesday, May 2nd

• Topics:
  • Multiple Linear Regression
• Read:
  • Chemometrics: 271-292
• Handouts:
  • none
• Homework:
  • none

Week Twelve

Monday, April 23rd (Note: bring computers to class)

• Topics:
  • Principal Component Analysis
• Read:
  • Chemometics: 183-199, 205-210
• Handouts:
  • Using R for a Principal Component Analysis
• Homework
  • none

Wednesday, April 25th

• Topics:
  • Pattern Recognition
• Read:
  • Chemometrics: 224-230
• Handouts:
  • none
• Homework
  • none

Week Eleven

Monday, April 16th

• Topics:
  • Signal Processing with Derivatives
• Read:
  • Chemometics: 138-142
• Handouts:
  • Raw Data
  • Background
  • Signal
  • First-Derivative of Raw Data
  • Second-Derivative of Raw Data
  • Coefficients for Savitsky-Golay Derivative Filtering
  • Overlapping Signals
• Homework
  • none

Wednesday, April 18th (Note: bring computers to class)

• Topics:
  • Principal Component Analysis
• Read:
  • Chemometrics: 183-199, 205-210
• Handouts:
  • PCA Example
• Homework
  • none

Week Ten

Monday, April 9th

• Topics:
  • Signals and Noise; Signal Processing
• Read:
  • Chemometrics: 122-125, 128-134, 147-150
  • Signal Smoothing Algorithms (text and applet)
  • Fourier Synthesis of Periodic Waveforms (text and applet)
  • Fourier Analysis and Signal Filtering (text and applet)
• Handouts:
  • Gaussian and Lorentzian Peaks
  • Homoscedastic and Heteroscedastic Noise
  • Signal-to-Noise Ratio Examples
  • Coefficients for Savitsky-Golay Filtering
  • Fourier Transform Example
• Homework:
  • none

Wednesday, April 11th (Note: bring computers to class)

• Topics:
  • Smoothing and Filtering Signals
• Read:
  • Chemometrics: 122-125, 128-134, 147-150
• Handouts:
  • Using R for Smoothing and Filtering
  • Creating 3-Dimensional Surface and Contour Plots in R
• Homework:
  • Long Problem Set 6

Week Nine

Monday, April 2nd

• Topics:
  • Evaluating Models; Fractional Experimental Designs
• Read: Chemometrics: 15-36, 53-69, 84-96
• Handouts:
  • Spectrophotometric Determination of Ceruloplasmin
  • Fractional Experimental Design
• Homework:
  • none

Wednesday, April 4th (Note: bring computers to class)

• Topics:
  • Evaluating Models for Curvature; Ruggedness Tesing
• Read:
  • Chemometrics: 15-36, 53-69, 84-96
• Handouts:
  • Plackett-Burman Design Exercise
  • Box-Behnken Design
  • Creating a Surface Plot in Excel
• Homework:
  • Short Problem Set 6
  • First Journal Article Summary

Week Eight

Monday, March 19th

• Topics:
  • Replication
• Read: none
• Handouts:
  • The Importance of Replicates in Regression
• Homework:
  • none

Wednesday, March 21st

• Topics:
  • Experimental Design: Factorial Designs
• Read:
  • Modern Analytical Chemistry: 667-671, 674-683
  • Brereton: Chapter 2: 15-36, 53-69, 84-96
• Handouts:
• Homework:
  • none

Week Seven

Monday, March 12th

• Topics:
  • Review for Midterm Exam

Wednesday, March14th

• Topics:
  • In-Class Midterm Exam
• Homework:
  • Take-Home Midterm Exam

Week Six

Monday, March 5th

• Topics:
  • Linear Regression
• Read:
  • Modern Analytical Chemistry: 117-127
  • How Linear Regression Works
• Handouts:
  • Derivation of Least-Squares for a Straight-Line
  • ANOVA and Regression
  • Regression Worksheet
• Homework:
  • Short Problem Set 5

Wednesday, March 7th (Note: bring computers to class)

• Topics:
  • Linear Regression Using R
• Read:
• Handouts:
  • Using R For a Linear Regression
• Homework:
  • Long Problem Set 5

Week Five

Monday, February 26th

• Class canceled - Pittsburgh Conference

Wednesday, February 28th (Note: bring computers to class)

• Topics:
  • Analysis of Variance Using R
• Read:
  • ANOVA/MANOVA (Statsoft; use link on right)
  • ANOVA (Hyperstat Online; Chapters 12 and 13)
• Handouts:
  • Using R for an Analysis of Variance
• Homework:
  • Long Problem Set 4

Week Four

Monday, February 19th (Note: bring computers to class)

• Topics:
  • Significance Testing with R
• Read:
  • Wilcoxon Signed Rank Test (read Basics and Logic sections)
  • Mann-Whitney Test (a slightly different formulation, but the same idea
• Handouts:
  • Significance Testing with R
  • Why Paired t-Tests are Important
• Homework:
  • Long Problem Set 3

Wednesday, February 21st

• Topics:
  • Analysis of Variance
• Read:
  • Modern Analytical Chemistry: 693-697
• Handouts:
  • Stability of Reagents Under Different Storage Conditions
• Homework:
  • Short Problem Set 4

Week Three

Monday, February 12th

• Topics:
  • Significance Tests
• Read:
  • Modern Analytical Chemistry: 82-94
• Handouts:
  • t-Table
  • F-table (one-sided)
  • F-table (two-sided)
  • Q-table
  • Summary of Significance Tests
• Homework:
  • Short Problem Set 3

Wednesday, February 14th (Note: bring computers to class)

• Class canceled due to University snow day

Week Two

Monday, February 5th

• Topics:
  • Distributions of Data
  • The Normal Distribution
  • Probability and the Normal Distribution
• Read:
  • Modern Analytical Chemistry: 70-75, 77-79
  • Chapter 5 - Normal Distribution (Hyperstat Online)
  • Why The Normal Distribution in Important (Statsoft Textbook; click on "General Concepts" and then "Why the 'Normal Distribution' is Important"
  • Central Limit Theorem (Applet; requires a java-enabled browser)
• Handouts:
  • Discrete and Binomial Distribution
  • Single-Sided Normal Distribution
• Homework:
  • Short Problem Set 2

Wednesday, February 7th (Note: bring computers to class)

• Topics:
  • Normal Probability Plots
  • Using R to Evaluate Probability for a Normal Distribution
• Read:
  • Q-Q Plots
• Handouts:
  • Probability and Normal Distributions With R
  • Graphing Data in R - A Gallery of Plots
  • Managing Graphics With R - The Basics
  • Managing Graphics With R - Adding Features to Graphs
• Homework:
  • Long Problem Set 2

Week One

Monday, January 29th

• Topics:
  • Course introduction
  • Basic descriptive statistics
• Read:
  • Modern Analytical Chemistry: 53-64
  • Box Plots (NIST Textbook)
  • Box Plots (StatSoft Textbook: click on Graphical Analysis: Box)
  • Box Plots (Hyperstat Textbook's Glossary)
  • Skewness & Kurtosis (NIST Textbook)
  • Skewness & Kurtosis (StatSoft Textbook's Statisical Glossary)
  • Skewness & Kurtosis (Hyperstat Textbook's Glossary)
• Handouts:
  • Syllabus
  • Sample data
  • Summary of Basic Descriptive Statistics
• Homework:
  • Short Problem Set 1
  • Download R to your computer (click here for instructions)

Wednesday, January 31st (Note: bring computers to class)

• Topics:
  • Basic descriptive statistics using R
• Handouts:
  • Some Basic R Commands
  • Basic Descriptive Statistics
  • Writing Functions In R
  • Using Data Frams and Indexing in R
• Homework:
  • Long Problem Set 1

last modified on May 5, 2007
send comments to David Harvey (harvey@depauw.edu)