Open Textbooks
Files
Download Full Text (9.9 MB)
Description
Lecture notes for Advanced Data Analysis (ADA1 Stat 427/527 and ADA2 Stat 428/528), Department of Mathematics and Statistics, University of New Mexico, Fall 2016-Spring 2017. Additional material including RMarkdown templates for in-class and homework exercises, datasets, R code, and video lectures are available on the course websites: https://statacumen.com/teaching/ada1 and https://statacumen.com/teaching/ada2 .
Contents
I ADA1: Software
- 0 Introduction to R, Rstudio, and ggplot
II ADA1: Summaries and displays, and one-, two-, and many-way tests of means
- 1 Summarizing and Displaying Data
- 2 Estimation in One-Sample Problems
- 3 Two-Sample Inferences
- 4 Checking Assumptions
- 5 One-Way Analysis of Variance
III ADA1: Nonparametric, categorical, and regression methods
- 6 Nonparametric Methods
- 7 Categorical Data Analysis
- 8 Correlation and Regression
- IV ADA1: Additional topics
- 9 Introduction to the Bootstrap
- 10 Power and Sample size
- 11 Data Cleaning
V ADA2: Review of ADA1
- 1 R statistical software and review
VI ADA2: Introduction to multiple regression and model selection
- 2 Introduction to Multiple Linear Regression
- 3 A Taste of Model Selection for Multiple Regression
VII ADA2: Experimental design and observational studies
- 4 One Factor Designs and Extensions
- 5 Paired Experiments and Randomized Block Experiments
- 6 A Short Discussion of Observational Studies
VIII ADA2: ANCOVA and logistic regression
- 7 Analysis of Covariance: Comparing Regression Lines
- 8 Polynomial Regression
- 9 Discussion of Response Models with Factors and Predictors
- 10 Automated Model Selection for Multiple Regression
- 11 Logistic Regression
IX ADA2: Multivariate Methods
- 12 An Introduction to Multivariate Methods
- 13 Principal Component Analysis
- 14 Cluster Analysis
- 15 Multivariate Analysis of Variance
- 16 Discriminant Analysis
- 17 Classification
Publication Date
Fall 2016
City
Albuquerque
Keywords
data visualization, classification, model checking
Disciplines
Applied Statistics | Design of Experiments and Sample Surveys | Multivariate Analysis | Statistical Methodology | Statistical Models
Recommended Citation
Erhardt, Erik B.; Edward J. Bedrick; and Ronald M. Schrader. "Advanced Data Analysis - Lecture Notes." (2016). https://digitalrepository.unm.edu/unm_oer/2
Included in
Applied Statistics Commons, Design of Experiments and Sample Surveys Commons, Multivariate Analysis Commons, Statistical Methodology Commons, Statistical Models Commons