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Exam A solutions
Exam B solutions
Syllabus STA121
Script STA121
Lecture slides
01 Slides Resampling
02 Slides PCA
03 Slides Clustering
04 Slides Classification
05 Slides Linear Model, cor p.8
06 Slides Mixed Models
07 Slides Non-parametric Regression
08 Slides Generalized linear model
09 Slides Survival Analysis
10 Slides Time Series Evaluation links
11 Slides Spatial Statistics
12 Slides Extreme Value Theory
13 Slides Neural Networks
14 Slides Summary
Lecture code
01 Resampling Code
02 PCA Code
03 Clustering Code
03 Clustering code, mbclust
04 Classification Code
05 Linear Model Code, cor. l24, l123
06 Linear Model quiz code
06 Mixed Models code
07 Non-parametric Regression Code
08 Generalized linear model code
09 Survival Analysis code
10 Time Series Code
11 Spatial Statistics Code
12 Extreme Value Theory Code
13 Neural Networks code
13 Neural networks code compiled
Exercise notes George
Code for 2nd exercise (George)
Code for 3rd exercise (George)
Code for 4th exercise (George)
Code for 5th exercise (George)
Code for 6th exercise (George)
Code for 7th exercise (George)
Code for 8th exercise (George)
Code for 9th exercise (George)
Code for 10th exercise (George)
Code for 12th exercise (George)
Exercise Notes Heng
How to use R markdown Heng Zhang
r basic intro week1
STA121_Exercise_Week03_HengZhang
STA121_Exercise_Week04_05_HengZhang
STA121_Exercise_Week09_HengZhang
STA121_Exercise_Week10_HengZhang
STA121_Exercise_Week11_HengZhang
STA121_Exercise_Week13_HengZhang
Extra Files
salary.txt
01 In Class Exercise
Syllabus
For further information please contact: Dr. Zofia Baranczuk
Module: 24.01.2022 13:30-16:30, Room: Y04G30 Seats: 577, Type: written examRepetition: 13.09.2022 9:00-12:00, Room: Y27H12 Seats: 50, Type: written exam
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