## Recently Published

##### Akaike's Information Criterion (AIC)

Introduction to Quantitative Biology (BIOL 325)
February 24, 2020
Spring 2020
William & Mary

##### Parsimony, Likelihood, and AIC

Introduction to Quantitative Biology (BIOL 325)
February 19, 2020
Spring 2020
William & Mary

##### Parsimony and Collinearity

Introduction to Quantitative Biology (BIOL 325)
February 17, 2020
Spring 2020
William & Mary

##### Data and Models

Introduction to Quantitative Biology (BIOL 325)
February 14, 2020
Spring 2020
William & Mary

##### Multiple Linear Regression (Part 2)

Introduction to Quantitative Biology (BIOL 325)
February 12, 2020
Spring 2020
William & Mary

##### Multiple Linear Regression

Introduction to Quantitative Biology (BIOL 325)
February 10, 2020
Spring 2020
William & Mary

##### Linear Regression (cont'd)

Introduction to Quantitative Biology (BIOL 325)
February 7, 2020
Spring 2020
William & Mary

##### Linear Regression

Introduction to Quantitative Biology (BIOL 325)
February 5, 2020
Spring 2020
William & Mary

##### Errors in Hypothesis Testing

Introduction to Quantitative Biology (BIOL 325)
February 3, 2020
Spring 2020
William & Mary

##### Central Limit Theorem and Hypothesis Testing

Introduction to Quantitative Biology (BIOL 325)
January 31, 2020
Spring 2020
William & Mary

##### Lecture 3: Sampling Distributions and Confidence Intervals

Introduction to Quantitative Biology (BIOL 325)
January 29, 2020
Spring 2020
William & Mary

##### Intro to Statistical Inference

Introduction to Quantitative Biology (BIOL 325)
January 27, 2020
Spring 2020
William & Mary

##### Understanding Science

Introduction to Quantitative Biology (BIOL 325)
January 27, 2020
Spring 2020
William & Mary

##### Lecture 33: Regression (Part 2)

Introduction to Biostatistics (BIOL 327)
December 6, 2019
Fall 2019
William & Mary

##### Lecture 32: Regression

Introduction to Biostatistics (BIOL 327)
December 4, 2019
Fall 2019
William & Mary

##### Lecture 31: Correlation between numerical variables

Introduction to Biostatistics (BIOL 327)
December 2, 2019
Fall 2019
William & Mary

##### Lecture 30: The Analysis of Variance (ANOVA) Part 3

Introduction to Biostatistics (BIOL 327)
November 20, 2019
Fall 2019
William & Mary

##### Lecture 29: The Analysis of Variance (ANOVA) Part 2 (edited)

Introduction to Biostatistics (BIOL 327)
November 20, 2019
Fall 2019
William & Mary

##### Lecture 29: The Analysis of Variance (ANOVA) Part 2

Introduction to Biostatistics (BIOL 327)
November 18-20, 2019
Fall 2019
William & Mary

##### Lecture 28: The Analysis of Variance (ANOVA)

Introduction to Biostatistics (BIOL 327)
November 18, 2019
Fall 2019
William & Mary

##### Lecture 27: My assumptions are violated!! (Part 2)

Introduction to Biostatistics (BIOL 327)
November 15, 2019
Fall 2019
William & Mary

##### Lecture 26: My assumptions are violated!!

Introduction to Biostatistics (BIOL 327)
November 13, 2019
Fall 2019
William & Mary

##### Lecture 25: Pseudoreplication and sampling

Introduction to Biostatistics (BIOL 327)
November 11, 2019
Fall 2019
William & Mary

##### Lecture 24: Variances, Fallacies, and Exams - Oh my!!!

Introduction to Biostatistics (BIOL 327)
November 6, 2019
Fall 2019
William & Mary

##### Lecture 23: Comparing two means (Part 2)

Introduction to Biostatistics (BIOL 327)
November 4, 2019
Fall 2019
William & Mary

##### Lecture 22: Comparing two means

Introduction to Biostatistics (BIOL 327)
November 1, 2019
Fall 2019
William & Mary

##### Lecture 21: Inference for a normal population

Introduction to Biostatistics (BIOL 327)
October 30, 2019
Fall 2019
William & Mary

##### Lecture 20: The normal distribution

Introduction to Biostatistics (BIOL 327)
October 28, 2019
Fall 2019
William & Mary

##### Contingency Analysis: Part 2

Introduction to Biostatistics (BIOL 327)
October 23, 2019
Fall 2019
William & Mary

##### Lecture 18: Contingency Analysis

Introduction to Biostatistics (BIOL 327)
October 21, 2019
Fall 2019
William & Mary

##### Lecture 16: Fitting probability models to frequency data (Part I)

Introduction to Biostatistics (BIOL 327)
October 16, 2019
Fall 2019
William & Mary

##### Lecture 15: Fitting probability models to frequency data (Part I)

Introduction to Biostatistics (BIOL 327)
October 11, 2019
Fall 2019
William & Mary

##### Lecture 14: Analyzing Proportions (Part 2)

Introduction to Biostatistics (BIOL 327)
October 9, 2019
Fall 2019
William & Mary

##### Lecture 13: Analyzing Proportions (Part 1)

Introduction to Biostatistics (BIOL 327)
October 7, 2019
Fall 2019
William & Mary

##### Lecture 12: Hypothesis Testing

Introduction to Biostatistics (BIOL 327)
October 4, 2019
Fall 2019
William & Mary

##### Lecture 11: Questions, Hypotheses, and Predictions

Introduction to Biostatistics (BIOL 327)
September 30, 2019
Fall 2019
William & Mary

##### Lecture 10.5: Bayes Theorem

Introduction to Biostatistics (BIOL 327)
September 30, 2019
Fall 2019
William & Mary

##### Lecture 10: Probability (Part 2)

Introduction to Biostatistics (BIOL 327)
September 20, 2019
Fall 2019
William & Mary

##### Lecture 9: Probability

Introduction to Biostatistics (BIOL 327)
September 18, 2019
Fall 2019
William & Mary

##### Lecture 8: Estimating with Uncertainty (Part 2)

Introduction to Biostatistics (BIOL 327)
September 16, 2019
Fall 2019
William & Mary

##### Lecture 7: Estimating with Uncertainty

Introduction to Biostatistics (BIOL 327)
September 13, 2019
Fall 2019
William & Mary

##### Lecture 6: Descriptive Statistics

Introduction to Biostatistics (BIOL 327)
September 11, 2019
Fall 2019
William & Mary

##### Lecture 5: Data Visualization (Part 2)

Introduction to Biostatistics (BIOL 327)
September 9, 2019
Fall 2019
William & Mary

##### Lecture 4: Data Visualization

Introduction to Biostatistics (BIOL 327)
September 4, 2019
Fall 2019
William & Mary

##### Lecture 3: What is statistics?

Introduction to Biostatistics (BIOL 327)
September 2, 2019
Fall 2019
William & Mary

##### Lecture 2: Intro to Data & Experimental Design

Introduction to Biostatistics (BIOL 327)
August 30, 2019
Fall 2019
William & Mary

##### Lecture 1: Intro to Course

Introduction to Biostatistics (BIOL 327)
August 29, 2019
Fall 2019
William and Mary

##### Population Genetics

Introduction to Quantitative Biology (BIOL 325)
March 27, 2019
Spring 2019
College of William and Mary

##### In Silico Experimentation

Introduction to Quantitative Biology (BIOL 325)
March 20, 2019
Spring 2019
College of William and Mary

##### Testing Your Program

Introduction to Quantitative Biology (BIOL 325)
March 18, 2019
Spring 2019
College of William and Mary

##### In-Silico Simulation: The 2019 Raft Debate Edition!

EDIT: Slide title is "Testing your Program", but this title is more appropriate to the content.
Introduction to Quantitative Biology (BIOL 325)
March 15, 2019
Spring 2019
College of William and Mary

##### Implementing and Testing an Agent-Based Model

Introduction to Quantitative Biology (BIOL 325)
March 13, 2019
Spring 2019
College of William and Mary

##### Describing and Formulating ABMs: The ODD Protocol

Introduction to Quantitative Biology (BIOL 325)
March 11, 2019
Spring 2019
College of William and Mary

##### Introduction to Agent-Based Modeling (ABM)

Introduction to Quantitative Biology (BIOL 325)
February 25, 2019
Spring 2019
College of William and Mary

##### Akaike's Information Criterion (AIC)

Introduction to Quantitative Biology (BIOL 325)
February 22, 2019
Spring 2019
College of William and Mary

##### Parsimony and Likelihood (Part 2)

Introduction to Quantitative Biology (BIOL 325)
February 20, 2019
Spring 2019
College of William and Mary

##### Parsimony and Likelihood

Introduction to Quantitative Biology (BIOL 325)
February 18, 2019
Spring 2019
College of William and Mary

##### Parsimony and Collinearity

Introduction to Quantitative Biology (BIOL 325)
February 15, 2019
Spring 2019
College of William and Mary

##### Data and Models

Introduction to Quantitative Biology (BIOL 325)
February 13, 2019
Spring 2019
College of William and Mary

##### Multiple Linear Regression (Part 2)

Introduction to Quantitative Biology (BIOL 325)
February 11, 2019
Spring 2019
College of William and Mary

##### Multiple Linear Regression (Part 1)

Introduction to Quantitative Biology (BIOL 325)
February 8, 2019
Spring 2019
College of William and Mary

##### Linear Regression (cont'd)

Introduction to Quantitative Biology (BIOL 325)
February 6, 2019
Spring 2019
College of William and Mary

##### Linear Regression

Introduction to Quantitative Biology (BIOL 325)
February 4, 2019
Spring 2019
College of William and Mary

##### Errors in Hypothesis Testing; Linear Regression

Introduction to Quantitative Biology (BIOL 325)
February 1, 2019
Spring 2019
College of William and Mary

##### Central Limit Theorem and Hypothesis Testing

Introduction to Quantitative Biology (BIOL 325)
January 30, 2019
Spring 2019
College of William and Mary

##### Sampling Distributions and Confidence Intervals

Introduction to Quantitative Biology (BIOL 325)
January 28, 2019
Spring 2019
College of William and Mary

##### Intro to Statistical Inference

Introduction to Quantitative Biology (BIOL 325)
January 25, 2019
Spring 2019
College of William and Mary

##### Intro to Models and Modeling

Introduction to Quantitative Biology (BIOL 325)
January 23, 2019
Spring 2019
College of William and Mary

##### Lecture 35: Parting words and stuff

Introduction to Biostatistics (BIOL 327)
December 7, 2018
Fall 2018
College of William and Mary

##### Lecture 34: Different experimental designs

Introduction to Biostatistics (BIOL 327)
December 5, 2018
Fall 2018
College of William and Mary

##### Lecture 33: Regression (Part 2)

Introduction to Biostatistics (BIOL 327)
December 3, 2018
Fall 2018
College of William and Mary

##### Lecture 32: Regression (Part 1)

Introduction to Biostatistics (BIOL 327)
November 28, 2018
Fall 2018
College of William and Mary

##### Lecture 31: Correlation

Introduction to Biostatistics (BIOL 327)
November 26, 2018
Fall 2018
College of William and Mary

##### Lecture 30: The Analysis of Variance (ANOVA) - Part 3

Introduction to Biostatistics (BIOL 327)
November 19, 2018
Fall 2018
College of William and Mary

##### Lecture 29: The Analysis of Variance (ANOVA) - Part 2

Introduction to Biostatistics (BIOL 327)
November 16, 2018
Fall 2018
College of William and Mary

##### Lecture 28: The Analysis of Variance (ANOVA) - Part 1

Introduction to Biostatistics (BIOL 327)
November 14, 2018
Fall 2018
College of William and Mary

##### Lecture 27: My assumptions are violated!! (Part 2)

Introduction to Biostatistics (BIOL 327)
November 12, 2018
Fall 2018
College of William and Mary

##### Lecture 26: My assumptions are violated!!

Introduction to Biostatistics (BIOL 327)
November 7, 2018
Fall 2018
College of William and Mary

##### Lecture 25: Pseudoreplication and sampling

Introduction to Biostatistics (BIOL 327)
November 5, 2018
Fall 2018
College of William and Mary

##### Lecture 24: Variances, Fallacies, and Exams - Oh my!!!

Introduction to Biostatistics (BIOL 327)
November 2, 2018
Fall 2018
College of William and Mary

##### Lecture 23: Comparing two means (unpaired designs)

Introduction to Biostatistics (BIOL 327)
October 31, 2018
Fall 2018
College of William and Mary

##### Lecture 22: Comparing two means (paired designs)

Introduction to Biostatistics (BIOL 327)
October 29, 2018
Fall 2018
College of William and Mary

##### Lecture 21: Inference for a normal population

Introduction to Biostatistics (BIOL 327)
October 24, 2018
Fall 2018
College of William and Mary

##### Lecture 20: The normal distribution

Introduction to Biostatistics (BIOL 327)
October 22, 2018
Fall 2018
College of William and Mary

##### Lecture 19: Contingency Analysis (Part 2)

Introduction to Biostatistics (BIOL 327)
October 19, 2018
Fall 2018
College of William and Mary

##### Lecture 18: Contingency Analysis

Introduction to Biostatistics (BIOL 327)
October 17, 2018
Fall 2018
College of William and Mary

##### Lecture 16: Fitting probability models to frequency data (Part 2)

Introduction to Biostatistics (BIOL 327)
October 10, 2018
Fall 2018
College of William and Mary

##### Lecture 15: Fitting probability models to frequency data (Part I)

Introduction to Biostatistics (BIOL 327)
October 8, 2018
Fall 2018
College of William and Mary

##### Lecture 14: Analyzing Proportions (Part 2)

Introduction to Biostatistics (BIOL 327)
October 5, 2018
Fall 2018
College of William and Mary

##### Lecture: Bayes Theorem

Introduction to Biostatistics (BIOL 327)
October 3, 2018
Fall 2018
College of William and Mary

##### Lecture 13: Analyzing proportions

Introduction to Biostatistics (BIOL 327)
October 3, 2018
Fall 2018
College of William and Mary

##### Lecture 12: Hypothesis Testing

Introduction to Biostatistics (BIOL 327)
October 1, 2018
Fall 2018
College of William and Mary

##### Lecture 11: Questions, Hypotheses, and Predictions

Introduction to Biostatistics (BIOL 327)
September 26, 2018
Fall 2018
College of William and Mary

##### Lecture 10: Probability (Part 2)

Introduction to Biostatistics (BIOL 327)
September 24, 2018
Fall 2018
College of William and Mary

##### Lecture 9: Probability (Part 1)

Slides: http://rpubs.com/mdlama/fall2018_lecture08
Introduction to Biostatistics (BIOL 327)
September 21, 2018
Fall 2018
College of William and Mary

##### Lecture 8: Estimating with Uncertainty (Part 2)

Introduction to Biostatistics (BIOL 327)
September 19, 2018
Fall 2018
College of William and Mary

##### Lecture 7: Estimating with Uncertainty (Part 1)

Introduction to Biostatistics (BIOL 327)
September 17, 2018
Fall 2018
College of William and Mary

##### Lecture 6: Descriptive Statistics

Introduction to Biostatistics (BIOL 327)
September 10, 2018
Fall 2018
College of William and Mary

##### Lecture 5: Data Visualization (Part 2)

Introduction to Biostatistics (BIOL 327)
September 7, 2018
Fall 2018
College of William and Mary

##### Lecture 4: Data Visualization

Introduction to Biostatistics (BIOL 327)
September 5, 2018
Fall 2018
College of William and Mary

##### Lecture 3: What is statistics?

Introduction to Biostatistics (BIOL 327)
September 3, 2018
Fall 2018
College of William and Mary

##### Lecture 2: Intro to Data & Experimental Design

Introduction to Biostatistics (BIOL 327)
August 31, 2018
Fall 2018
College of William and Mary

##### Lecture 1: Intro to Course

Introduction to Biostatistics (BIOL 327)
August 29, 2018
Fall 2018
College of William and Mary

##### Lecture 35: Different experimental designs

Introduction to Biostatistics (BIOL 327)
April 19, 2017
Spring 2017
College of William and Mary

##### Lecture 34: Multiple explanatory variables (Part 2)

Introduction to Biostatistics (BIOL 327)
April 17, 2017
Spring 2017
College of William and Mary

##### Lecture 33: Multiple explanatory variables (Part 1)

Introduction to Biostatistics (BIOL 327)
April 14, 2017
Spring 2017
College of William and Mary

##### Lecture 32: Regression (Part 2)

Introduction to Biostatistics (BIOL 327)
April 12, 2017
Spring 2017
College of William and Mary

##### Lecture 31: Regression (Part 1)

Introduction to Biostatistics (BIOL 327)
April 10, 2017
Spring 2017
College of William and Mary

##### Lecture 30: Correlation between numerical variables

Introduction to Biostatistics (BIOL 327)
April 7, 2017
Spring 2017
College of William and Mary

##### Lecture 29: The Analysis of Variance (Part 3)

Introduction to Biostatistics (BIOL 327)
April 5, 2017
Spring 2017
College of William and Mary

##### Lecture 28: The Analysis of Variance (ANOVA) (Part 2)

Introduction to Biostatistics (BIOL 327)
April 3, 2017
Spring 2017
College of William and Mary

##### Lecture 27: The Analysis of Variance (ANOVA)

Introduction to Biostatistics (BIOL 327)
March 31, 2017
Spring 2017
College of William and Mary

##### Lecture 26: My assumptions are violated! (Part 2)

Introduction to Biostatistics (BIOL 327)
March 29, 2017
Spring 2017
College of William and Mary

##### Lecture 25: My assumptions are violated!

Introduction to Biostatistics (BIOL 327)
March 28, 2017
Spring 2017
College of William and Mary

##### Lecture 24: Pseudoreplication and sampling

Introduction to Biostatistics (BIOL 327)
March 22, 2017
Spring 2017
College of William and Mary

##### Lecture 23: Comparing two means (Part 2)

Introduction to Biostatistics (BIOL 327)
March 20, 2017
Spring 2017
College of William and Mary

##### Lecture 22: Comparing two means (paired designs)

Introduction to Biostatistics (BIOL 327)
March 17, 2017
Spring 2017
College of William and Mary

##### Lecture 21: Inference for a Normal Population

Introduction to Biostatistics (BIOL 327)
March 15, 2017
Spring 2017
College of William and Mary

##### Lecture 20: The normal distribution

Introduction to Biostatistics (BIOL 327)
March 13, 2017
Spring 2017
College of William and Mary

##### Lecture 19: Contingency Analysis (Part 2)

Introduction to Biostatistics (BIOL 327)
March 3, 2017
Spring 2017
College of William and Mary

##### Mass extinctions with matrix/table

Introduction to Biostatistics (BIOL 327)
March 3, 2017
Spring 2017
College of William and Mary

##### Lecture 18: Contingency Analysis

Introduction to Biostatistics (BIOL 327)
March 1, 2017
Spring 2017
College of William and Mary

##### Mass extinctions with dplyr and tidyr

Introduction to Biostatistics (BIOL 327)
March 1, 2017
Spring 2017
College of William and Mary

##### How do I get P-values and critical values from R?

Introduction to Biostatistics (BIOL 327)
March 1, 2017
Spring 2017
College of William and Mary

##### Lecture 17: Fitting probability models to frequency data (Part 2)

Introduction to Biostatistics (BIOL 327)
February 27, 2017
Spring 2017
College of William and Mary

##### Lecture 16: Fitting probability models to frequency data (Part 1)

Introduction to Biostatistics (BIOL 327)
February 24, 2017
Spring 2017
College of William and Mary

##### Lecture 15: Analyzing Proportions (Part 2)

Introduction to Biostatistics (BIOL 327)
February 22, 2017
Spring 2017
College of William and Mary

##### Lecture 14: Analyzing Proportions (Part 1)

Introduction to Biostatistics (BIOL 327)
February 22, 2017
Spring 2017
College of William and Mary

##### Lecture 12: Hypothesis Testing

Introduction to Biostatistics (BIOL 327)
February 13, 2017
Spring 2017
College of William and Mary

##### Lecture 11: Questions, Hypotheses, and Predictions

Introduction to Biostatistics (BIOL 327)
February 10, 2017
Spring 2017
College of William and Mary

##### Lecture 10: Probability (Part 2)

Introduction to Biostatistics (BIOL 327)
February 8, 2017
Spring 2017
College of William and Mary

##### Lecture 9: Probability

Introduction to Biostatistics (BIOL 327)
February 6, 2017
Spring 2017
College of William and Mary

##### Lecture 8: Estimating with Uncertainty (Part 2)

Introduction to Biostatistics (BIOL 327)
February 3, 2017
Spring 2017
College of William and Mary

##### Lab #3 Discussion: R-Markdown and Programming

Introduction to Biostatistics (BIOL 327)
February 2, 2017
Spring 2017
College of William and Mary

##### Lecture 7: Estimating with Uncertainty

Introduction to Biostatistics (BIOL 327)
February 1, 2017
Spring 2017
College of William and Mary

##### Lecture 6: Descriptive Statistics

Introduction to Biostatistics (BIOL 327)
January 27, 2017
Spring 2017
College of William and Mary

##### Lecture 5: Visualizing Data (Part 2)

Introduction to Biostatistics (BIOL 327)
January 27, 2017
Spring 2017
College of William and Mary

##### Lecture 4: Visualizing Data

Introduction to Biostatistics (BIOL 327)
January 25, 2017
Spring 2017
College of William and Mary

##### Lecture 3: What is Statistics?

Introduction to Biostatistics (BIOL 327)
January 23, 2017
Spring 2017
College of William and Mary

##### Lecture 2: Intro to Data & Experimental Design

Introduction to Biostatistics (BIOL 327)
January 20, 2017
Spring 2017
College of William and Mary

##### Lecture 1: Intro to Course

Introduction to Biostatistics (BIOL 327)
January 18, 2017
Spring 2017
College of William and Mary

##### Introduction to Systems Biology (cont'd)

from Introduction to Quantitative Biology
College of William and Mary
Fall 2016

##### Introduction to Systems Biology

Chapter 1: Ingalls
Introduction to Quantitative Biology
College of William and Mary
Fall 2016

##### Natural Selection

Introduction to Quantitative Biology
Fall 2016

##### In Silico Experimentation (cont'd)

Railsback & Grimm, Chapter 8
Introduction to Quantitative Biology
Fall 2016

##### In Silico Experimentation

Railsback & Grimm, Chapter 8
Introduction to Quantitative Biology
Fall 2016

##### Testing your program (cont'd)

Railsback & Grimm, Chapter6
Introduction to Quantitative Biology
Fall 2016

##### Testing your program

Railsback & Grimm, Chapter 6
Introduction to Quantitative Biology
Fall 2016

##### Implementing and Testing an Agent-Based Model

Railsback & Grimm, Chapters 3-5
Introduction to Quantitative Biology
Fall 2016

##### Describing and Formulating ABMs: The ODD Protocol

Introduction to Quantitative Biology
Fall 2016
The College of William and Mary

##### Introduction to Agent-Based Modeling (ABM)

Introduction to Quantitative Biology
Fall 2016

##### Information Theory: Practice

Working through hardening cement data.
Introduction to Quantitative Biology
Fall 2016

##### Parsimony and Collinearity

Chapter 2: Anderson, Model Based Inference in the Life Sciences
Introduction to Quantitative Biology
College of William and Mary
Fall 2016

##### Data and Models

Chapter 2: Anderson, Model Based Inference in the Life Sciences
Introduction to Quantitative Biology
College of William and Mary
Fall 2016

##### Multiple regression

OpenStats: Chapter 8
Introduction to Quantitative Biology
College of William and Mary
Fall 2016

##### Linear Regression

BIOL 325: Introduction to Quantitative Biology
Fall 2016
College of William and Mary
M. Drew LaMar

##### Errors in Hypothesis Testing; Linear Regression

Introduction to Quantitative Biology
Fall 2016
M. Drew LaMar

##### Central Limit Theorem and Hypothesis Testing

Introduction to Quantitative Biology
Fall 2016
M. Drew LaMar
OpenIntro Statistics: Chapter 4

##### Sampling Distributions and Confidence Intervals

M. Drew LaMar
Introduction to Quantitative Biology
Fall 2016
OpenIntro Statistics: Chapter 4

##### Intro to Statistical Inference

Lecture Slides (08-31-2016)
M. Drew LaMar
Introduction to Quantitative Biology, Fall 2016
College of William and Mary

##### Intro to Models and Modeling

Lecture Slides
Introduction to Quantitative Biology, Fall 2016
College of William and Mary

##### Introduction to Biostatistics at William and Mary - Spring 2016

Wasserstein, Ronald L., and Nicole A. Lazar. "The ASA's statement on p-values: context, process, and purpose." The American Statistician just-accepted (2016).

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 18: Multiple explanatory variables (cont'd)

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 18: Multiple explanatory variables (cont'd)

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 18: Multiple explanatory variables

##### Multiple explanatory variables: R code for Chapter 18 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter
Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode18

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 17: Regression (cont'd)

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 17: Regression

##### Regression: R code for Chapter 17 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter
Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode17

##### Correlation between numerical variables: R code for Chapter 16 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter
Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode16

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 15: Correlation between numerical variables

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 15: The analysis of variance (cont'd)
Planned, unplanned comparisons, and random effects ANOVA

##### Comparing means of more than two groups: R code for Chapter 15 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter
Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode15

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 15: The analysis of variance

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 15: The analysis of variance (Part II)
Up to planned and unplanned comparisons

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 13: Handling violations of assumptions (cont'd)

##### Handling violations of assumptions: R code for Chapter 13 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter
Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode13

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 13: Handling violations of assumptions

##### Introduction to Biostatistics at William and Mary - Spring 2016

Ruxton & Colegrave, Chapter 3: Between-individual variation, replication, and sampling

##### Introduction to Biostatistics at William and Mary - Spring 2016

Ruxton & Colegrave, Chapter 3: Between-individual variation, replication, and sampling

##### Comparing two means: R code for Chapter 12 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter
Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode12

##### Inference for a normal population: R code for Chapter 11 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode11

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 12: Comparing two means
Two-sample t-test; Welch's t-test

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 12: Comparing two means
Paired designs

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 11: Inference for a normal population

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 10: The normal distribution

##### The normal distribution: R code for Chapter 10 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter
Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode10

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 9

##### Contingency analysis: R code for Chapter 9 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter
Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode09

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 8: Fitting probability models to frequency data
Whitlock & Schluter, Chapter 9: Contingency analysis

##### Fitting probability models to frequency data: R code for Chapter 8 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter
Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode08

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 8 (cont'd)
PDF, CDF, CCDF, QF, and CQF

##### Introduction to Biostatistics at William and Mary - Spring 2016

Errors in hypothesis testing and statistical power
Whitlock & Schluter, Chapter 8: Fitting probability models to frequency data

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 7: Analyzing proportions
Binomial distribution and binomial test

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 7: Analyzing proportions

##### Introduction to Biostatistics at William and Mary - Spring 2016

Bayes Theorem and Medical Testing

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 7: Analyzing proportions

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 6: Hypothesis testing

##### Hypothesis testing: R code for Chapter 6 examples

This document was converted to R-Markdown by M. Drew LaMar from http://whitlockschluter.zoology.ubc.ca/r-code/rcode06.

##### Introduction to Biostatistics at William and Mary - Spring 2016

Ruxton & Colegrave, Chapter 2: Starting with a well-defined hypothesis

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 5: Probability (cont'd)

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 5: Probability

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 4: Estimating with uncertainty

##### Introduction to Biostatistics at William and Mary - Spring 2016

Introduction to course

##### Introduction to Biostatistics at William and Mary - Spring 2016

Ruxton & Colegrave, Chapter 1: Why you should care about design

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 1: Statistics and samples

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 2: Displaying data

##### Introduction to Biostatistics at William and Mary - Spring 2016

Whitlock & Schluter, Chapter 4: Estimating with uncertainty

##### Introduction to Quantitative Biology at William and Mary - Spring 2016

Descriptive statistics
Whitlock & Schluter, Chapter 3

##### Estimating with uncertainty: R code for Chapter 4 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter
Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode04

##### Describing data: R code for Chapter 3 examples

from textbook "The Analysis of Biological Data", by Whitlock and Schluter
Original R code located at http://whitlockschluter.zoology.ubc.ca/r-code/rcode03

##### Displaying data: R code for Chapter 2 examples

from textbook "The Analysis of Biological Data", by Whitlock & Schluter
Original R code available at http://whitlockschluter.zoology.ubc.ca/r-code/rcode02

##### Data visualization (Part 2)

Course: Introduction to Biostatistics at The College of William and Mary, Spring 2016