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  Advanced Data Analysis - Lecture Notes

  Erik B. Erhardt, Edward J. Bedrick, and Ronald M. Schrader

  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

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  Principles of Stable Isotope Geochemistry, 2nd Edition

  Zachary Sharp

  Principles of Stable Isotope Geochemistry is written as a textbook to accompany a one semester course in Stable Isotope Geochemistry. There are 13 chapters, each dealing with a specific subtopic of the field. Other than Chapters 1 and 2 – introduction and definitions – most of the remaining chapters can be read without reliance on the preceding ones. It is also hoped that the book will serve as a general reference volume for researchers in the field.

  Principles of Stable Isotope Geochemistry has been organized in such a way that major concepts are explained and accompanied by numerous examples. In most cases, the first published examples are used for illustration, giving both a broad base of understanding and an appreciation for the historical development of the field. Chapters are organized according to broad classifications. In some cases this is done by discipline such as Chapter 4 – Hydrology and in others by isotope, such as Chapter 10 – Sulfur. The new revised version is online. In this way, it can be modified as new advances are made in the field. Comments regarding errors, omissions or suggestions for improvements are welcome in order to keep the book up to date. This new online version is free of charge, available in PDF format. A hardcopy is also available.