# Advanced Data Analysis - Lecture Notes

## 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

• 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
• 9 Introduction to the Bootstrap
• 10 Power and Sample size
• 11 Data Cleaning

• 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

• 12 An Introduction to Multivariate Methods
• 13 Principal Component Analysis
• 14 Cluster Analysis
• 15 Multivariate Analysis of Variance
• 16 Discriminant Analysis
• 17 Classification

Fall 2016

Albuquerque

## Keywords

data visualization, classification, model checking

## Disciplines

Applied Statistics | Design of Experiments and Sample Surveys | Multivariate Analysis | Statistical Methodology | Statistical Models

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