MATH 6395 Calendar

Monday

Wednesday

Additional Info/Questions?

Jan 16
No Class

Jan 18
Introduction
The Data matrix, Descriptive Statistics
(1.3)
Linear Algebra Review: Chapter 2 p. 55-61, p. 84-86, p. 89-93

Jan 23
Discriptive Display, Linear combinations and Spectral Decomposition
(1.4, p.62)

Jan 25
Principal Components
(8.3)
HW#1
Here is the planets.data
from the planets class handout
Use the read.table command in R to read in the data into an R object, i.e..
> planets <- read.table("http://www-math.cudenver.edu/ ~bbailey/6395/ex_planets.data", header=T)
Take a look at the famous iris data
To view the Rotating point cloud you need to install Cortona VRML, it installs very easily from Cortona website

Jan 30
Principal Components (cont.)
(8.3)

Feb 1
Principal Components
(8.3)
HW#2
Class PCA Example using USArrests data set
R code pca_ex1.r
R output pca_ex1.out
R plots pca_plot1.pdf

Feb 6
Multivariate Distributions
(2.5-2.6, 3.3)

Feb 8
Multivariate Normal Distribution
(4.1-4.2))
HW#3
HW#3 Problem 4 Correction: the model for Y_j, the subscript on E should be j not J

Feb 13
Multivariate Normal Distribution
(4.1-4.4)

Feb 15
Multivariate Normal Distribution
(4.1-4.4, 4.6)
HW#4
HW#4 Problem 4: The qqnorm function makes a plot, so you don't have to use qqplot!

Feb 21
No Class!

Feb 23
Bivariate and Conditional, Normal Distribution
(4.1-4.4)
HW#5
bvnorm_plot.r should now be available!

Feb 27
Mutivariate Normal Distribution
p. 163

March 1
Mutlple Linear Regression and Least Squares
(7.1-7.4)
HW#6
.

March 6
Inferences About the Regression Model
(7.4)

March 8
Confidence Intervals Simple Linear Regression and Model Checking
(7.6)
No homework due next week!
In-class Midterm March 15
.

March 13
Simple Regression (cont.)
Midterm Exam Review Topics

March 15
In-class Midterm Exam,
You may use:
1 sheet (8 1/2 x 11) two-side of notes
and Calculator
.

March 27
Model Diagnostics
(7.6)

March 29
Model Selection
HW#7
see R help files for plot.lm, extractAIC
Class Climate Example: R code climate_ex.r
R plots climate_plots.pdf

April 3
Inferences about a Mean Vector
(5.1-5.2)

April 5
Likelihood Ratio Tests
(5.3,5.4)
HW#8
Class Exercise5.9 Example: R code plot_ex5.9.r
R plots 5.9.fig.pdf

April 10
Simultaneous Confidence Intervals
(5.4,5.5)

April 12
Testing Mean Vectors
(6.1-6.3)
HW#9
.

April 17
ANOVA and MANOVA (one-way)
(6.4)

April 19
MANOVA and Covariance Models

HW#10
Class MANOVA Example: R code sumcr_ex.r.r

April 24
MANOVA Models
(Chapter 6)

April 26
MANOVA Models
Extra Problems (not to be turned in!)
Class Mouth Data Example: Mouth Data mouths.txt
R code mouths.r
R output mouths.out
R plots mouths.pdf

May 1
Classification, Mixure Models and LDA
(Chapter 11)

May 3
Linear Discriminant Analysis
(Chapter 11)
Take-home Final Exam , due Thurs. May 11, by 5PM
R functions: lda, kmeans, and hclust (see help files)
Here is the HW#10 Solutions (pdf) Thanks Hyunmin!

Monday	Wednesday	Additional Info/Questions?
Jan 16 No Class	Jan 18 Introduction The Data matrix, Descriptive Statistics (1.3)	Linear Algebra Review: Chapter 2 p. 55-61, p. 84-86, p. 89-93
Jan 23 Discriptive Display, Linear combinations and Spectral Decomposition (1.4, p.62)	Jan 25 Principal Components (8.3) HW#1	Here is the planets.data from the planets class handout Use the read.table command in R to read in the data into an R object, i.e.. > planets <- read.table("http://www-math.cudenver.edu/ ~bbailey/6395/ex_planets.data", header=T) Take a look at the famous iris data To view the Rotating point cloud you need to install Cortona VRML, it installs very easily from Cortona website
Jan 30 Principal Components (cont.) (8.3)	Feb 1 Principal Components (8.3) HW#2	Class PCA Example using USArrests data set R code pca_ex1.r R output pca_ex1.out R plots pca_plot1.pdf
Feb 6 Multivariate Distributions (2.5-2.6, 3.3)	Feb 8 Multivariate Normal Distribution (4.1-4.2)) HW#3	HW#3 Problem 4 Correction: the model for Y_j, the subscript on E should be j not J
Feb 13 Multivariate Normal Distribution (4.1-4.4)	Feb 15 Multivariate Normal Distribution (4.1-4.4, 4.6) HW#4	HW#4 Problem 4: The qqnorm function makes a plot, so you don't have to use qqplot!
Feb 21 No Class!	Feb 23 Bivariate and Conditional, Normal Distribution (4.1-4.4) HW#5	bvnorm_plot.r should now be available!
Feb 27 Mutivariate Normal Distribution p. 163	March 1 Mutlple Linear Regression and Least Squares (7.1-7.4) HW#6	.
March 6 Inferences About the Regression Model (7.4)	March 8 Confidence Intervals Simple Linear Regression and Model Checking (7.6) No homework due next week! In-class Midterm March 15	.
March 13 Simple Regression (cont.) Midterm Exam Review Topics	March 15 In-class Midterm Exam, You may use: 1 sheet (8 1/2 x 11) two-side of notes and Calculator	.
March 27 Model Diagnostics (7.6)	March 29 Model Selection HW#7	see R help files for plot.lm, extractAIC Class Climate Example: R code climate_ex.r R plots climate_plots.pdf
April 3 Inferences about a Mean Vector (5.1-5.2)	April 5 Likelihood Ratio Tests (5.3,5.4) HW#8	Class Exercise5.9 Example: R code plot_ex5.9.r R plots 5.9.fig.pdf
April 10 Simultaneous Confidence Intervals (5.4,5.5)	April 12 Testing Mean Vectors (6.1-6.3) HW#9	.
April 17 ANOVA and MANOVA (one-way) (6.4)	April 19 MANOVA and Covariance Models HW#10	Class MANOVA Example: R code sumcr_ex.r.r
April 24 MANOVA Models (Chapter 6)	April 26 MANOVA Models Extra Problems (not to be turned in!)	Class Mouth Data Example: Mouth Data mouths.txt R code mouths.r R output mouths.out R plots mouths.pdf
May 1 Classification, Mixure Models and LDA (Chapter 11)	May 3 Linear Discriminant Analysis (Chapter 11) Take-home Final Exam , due Thurs. May 11, by 5PM	R functions: lda, kmeans, and hclust (see help files) Here is the HW#10 Solutions (pdf) Thanks Hyunmin!