Statistical Methods for Computer Science, Spring 2020

Schedule is updated dynamically throughout the semester

DATE TOPIC READING OUT DUE
Tue, Jan 7 1 One-variable regression:
estimation
KNNL Ch 1
Thu, Jan 9 2 One-variable regression:
associations, sampling distributions
KNNL Ch 2
Points of significance
Hw1 out
Tue, Jan 14 No class
make-up lecture TBA
Thu, Jan 16 Sampling distribution KNNL Ch. 2
Mon, Jan 20 Make-up lecture
Interval estimation
KNNL Ch. 2
Points of significance
Tue, Jan 21 Hypothesis testing KNNL Ch. 2
Points of significance
NMethods
Thu, Jan 23 Statistical power KNNL Ch. 2
Points of significance
Tue, Jan 28 3 General linear tests KNNL Ch. 2, 3.7 Hw2 out Hw1 due
Thu, Jan 30 Regression vs correlation:
Bivariate Normal
KNNL Ch. 2.11
Tue, Feb 4 4 Simultaneous inference KNNL Ch. 5
Thu, Feb 6 5 Projects: Cody Dunne
Multiple regression

KNNL Ch. 5-7
Tue, Feb 11 Project: Laura South Hw2 due
Proj group due
Thu, Feb 13 Midterm
Tue, Feb 18 Extra sums of squares
Categorial predictors
KNNL Ch. 7.1-7.4,
KNNL Ch. 8, Ch. 10.1
Thu, Feb 20 Experimental design KNNL Ch. 15-18
Tue, Feb 25 Project prep
Thu, Feb 27 Project pitches Fri Feb 28
Proj proposal due
Tue, Mar 3 Spring break
Thu, Mar 5 Spring break
Tue, Mar 10 Guest lecture
Designed experiments
and causal inference
Thu, Mar 12 Designed experiments:
1-factor ANOVA
KNNL Ch.15-18 Hw3 out
Tue, Mar 17 Designed experiments:
2-factor ANOVA
KNNL Ch.19
Thu, Mar 19 Designed experiments:
2-factor ANOVA
KNNL Ch.19
Tue, Mar 24 2-factor ANOVA
Pairwise comparisons
KNNL Ch.19 Wed Mar 25
Hw3 due
Thu, Mar 26 Speciailzed designs KNNL Ch. 20, 21,
Tue, Mar 31 Speciailzed designs KNNL Ch. 23, 24, 30 Hw4 out
Thu, Apr 2 Categorical data: associations Agresti Ch. 1-3
Faraway Ch. 4
Tue, Apr 7 Categorical data: associations
Thu, Apr 9 Inference in logistic regression KNNL Ch. 14
Faraway Ch.2
Agresti Ch.5-6
Tue, Apr 14 Inference in logistic regression Tue Apr 14
Hw4 due
Thu, Apr 16 Final exam
Tue, Apr 21 Project presentations Wed Apr 22
Proj report due
Thu, Apr 23
Proj review due