Overview  |  RenR 480  |  RenR 690  |  RenR 603  |  Pl Sc 221  |  R Graphics  |  Various


REN R 480/580 - Applied statistics for the environmental sciences (Fall Terms)

Course Instructor: Dr. Andreas Hamann, GSB 739, 492-6429, andreas.hamann@ualberta.ca

Location & Time: GSB 866, Tuesday & Thursday 8:00 to 9:20am, Thursday 12:30-1:50pm.

Course Information: The course focuses on problem formulation, method selection, and interpretation of statistical analysis. Covers data management and data visualization, statistical tests for parametric, non-parametric and binomial data, linear and non-linear regression approaches. Participants of the REN R 480 section will gain general statistical literacy and learn how to visualize and analyze data with open-source software packages. Participants in the RENR 580 section will also engage in problem-based learning by analyzing data from their thesis research project. Graduate students without a suitable dataset should enroll in two or more ★1 modules from the REN R 581/582/585/586 options instead. Prerequisite: a minimum of ★60 of university-level courses; ★3 introductory statistics recommended.

Fall 2018 Class Schedule

This material only applies to students in Section I, taught by Hamann. For Section II taught by Jaime Sebastian Azcona, visit this page.


Date
Lectures Labs Download
Sep 4
Inroduction & course overview, linking statistics and science, scientific hypotheses   Syllabus:
Sep 4 AM: pps
Sep 6-13
Unit 1. Data management
Statistical vocabulary, data table concept, variable types, basic data management
Intro to R & RStudio, data formatting and import, subset, merge, transform data
Sep 6: pps,pdf
Sep 11: WB,pdf, pdf
Sep 13: WB, pps, pps, pdf, pdf
R Cheat Sheet: pdf
Sep 19
Unit 2. Exploratory graphics
Data checking, data cleaning, display of raw data, diagnostic plots
R: plot, pairs, sunflowerplot, boxplot, hist
Sep 18: pdf, pdf, WB
Reading: si
Sep 20 - 25
Unit 3. Descriptive statistics
Measures of spread, shape and central tencency, degrees of freedom, central limit theorem
R: summary statistics (mean, sd, etc.) and pivot tables (group_by, summarize)
Excel: Pivot tables
Sep 20 AM/PM: WB, WB
Sep 20 Lab: pdf, pdf
Sep 25: WB
Assignment 1: pdf, pdf
Sep 27 - Oct 4
Unit 4. Presentation of quantitative data
Scatter, line, bar, and dot plots, multi-panel plots, graphic customizations.
Scientific graphs in R
Sep 27 AM: WB, link, pdf, pdf
Sep 27 PM: link, pdf, pdf
Oct 2: WB, pdf, pdf
Oct 4 AM: WB, pdf, pdf
Oct 4
Support session Projects, Labs, Assignments, Website
Graphics touch-up: pdf
Project guidelines: pdf, pps
Website, Weebly: pdf, pps
Assignment 2: pdf, pdf
Oct 9-18
Unit 5. Principles of inferential statistics
SE, CI, T-Test, Hypothesis testing

R: pnorm, qnorm, pt, qt, t.test

Oct 9, 11 AM: WB
Oct 11 PM: WB, pdf
Oct 16: WB
Oct 18 AM: WB
Reading: si, si
Oct 18
Unit 6. Analysis of variance
One-way ANOVA, pairwise comparisons

R: pf, qf, lm, lsmeans, cld
SAS: GLM

Oct 18 PM: WB, pdf, pdf
Oct 23
RENR711: project support
(no class for RENR480)
RENR711 project support
(no class for RENR480)
Presentation: link, link, link
Website: pps,pdf
Export graphics: pdf
Oct 26
RENR711: draft presentations
(no class for RENR480)
Previous Projects
Draft website due Oct 28, 23:59
Project Guidelines: pdf
Oct 20 & Nov 1
Unit 6. continued
Two-way ANOVA, assumptions, transformations

R: pf, qf, lm, lsmeans, cld

Oct 30: WB
Reading: si, si
Nov 1 AM: WB, WB
Nov 1 PM: WB, pdf, pdf
Nov 6
Unit 7. Experimental design
Blocking, covariates, unbalanced designes, lsmeans, mixed models, fixed and random effects, BLUPs and BLUEs

R: lme4, lmerTest, lmer, lsmeans, fixef, ranef, asreml

Nov 6: WB,pdf, pdf
Optional: pdf
Nov 8
Unit 8. Non-parametric tests
Wilcox rank sum, Kolmogorov-Smirnov, Kruskal-Wallis, permutational ANOVA
R: wilcox, ks, kruskal, friedman, aovp Nov 8, AM: WB, pdf, pdf
Nov 8, PM: WB
Nov 13, 15
Fall Term Break No Classes
Nov 20-22
Unit 9. Regression and correlation analysis
Pearson correlation, linear regression, non-parametric regression, non-linear regression, bootstrapping
R: corr, lm, nls, AIC, boot
Nov 20: WB, pdf, pdf
Assignment 3: pdf, pdf
Nov 22AM: WB, pdf, pdf
Nov 22
Unit 10. Tests for proportions
Chi-square test and z-test for proportions
R: prop, chisq, z.score

Nov 22PM: WB, pdf
Nov 27
Guidlines for exam prep, course notes, and projects Project & assignment support. Opporunity for Q&A on all lecture topics Course notes guidelines: pdf
Overview of techniques: WB
Nov 29
Project & assignment support AM & PM
Project & assignment support. Opporunity for Q&A on all lecture topics AM & PM
 
Dec 4
7:30am Start
RENR711: final presentations
(no class for RENR480)
Previous Projects
RENR 711 students: Final project due Dec 10, 11:59pm (deadline extended)
Project guidelines: pdf
Dec 6
Final exam at 8am to 9:20am in classroom GSB866 RENR 480 students: Course notes due Dec 6, 8:00am (in classroom before exam)
Sample Questions: pdf


Fall 2017 Class Schedule

This material only applies to students in Section I, taught by Hamann. For Section II taught by Montwe, visit this page.


Date
Lectures Labs Download
Sep 5
Inroduction & course overview, linking statistics and science, scientific hypotheses   Syllabus:
Sep 5 AM: pps
Sep 6-13
Unit 1. Data management
Statistical vocabulary, data table concept, variable types, basic data management
Intro to R & SAS, data formatting and import, subset, merge, transform data
Sep 7 AM: pps,pdf
Sep 12: WB,pdf
Sep 15: WB,pps
R Cheat Sheet: pdf
Sep 19
Unit 2. Exploratory graphics
Data checking, data cleaning, display of raw data
R: plot, boxplot, hist
SAS: HIST, GPLOT, BOXPLOT
Sep 19: pdf, pdf, WB
Reading: si
Sep 21 - 25
Unit 3. Descriptive statistics
Measures of spread, shape and central tencency, degrees of freedom, central limit theorem
R: aggregate, mean, sd, etc.
SAS: UNIVARIATE
Excel: Pivot tables
Sep 21-25: WB, WB, WB
Sep 21: pdf, pdf
Assignment 1: pdf
Sep 28 - Oct 5
Unit 4. Presentation of quantitative data
Scatter, line, bar, and dot plots, multi-panel plots, graphic customizations.
Scientific graphs in R
Sep 28 AM: WB, pdf, pdf
Sep 28 PM: pdf
Oct 3: pdf, pdf
Oct 5 AM: pdf, pdf
Reading: si, si, si
Oct 5
Support session Projects, Labs, Assignments, Website
Assignment 2: pdf, pdf
Project guidelines: pdf, pps,pdf
Weebly 2016: pps
Oct 10-19
Unit 5. Principles of inferential statistics
SE, CI, T-Test

R: pnorm, qnorm, pt, qt, t.test, lm
SAS: TTEST, GLM

Oct 10, 12 AM: WB
Oct 12 PM: WB, pdf
Oct 17, 19: WB, WB
Reading: si, si
Oct 19
Unit 6. Analysis of variance
One-way ANOVA

R: pf, qf, lm,

Oct 19 AM: WB, pdf, pdf
Oct 24
RENR711: project support
(no class for RENR480)
RENR711 project support
(no class for RENR480)
Presentation: link, link, link
Website: pps,pdf
Export graphics: pdf
Oct 26
RENR711: draft presentations
(no class for RENR480)
Previous Projects
Draft Project due Oct 26
Project Guidelines: pdf
Oct 20 & Nov 1
Unit 6. continued
Two-way ANOVA, assumptions, transformations

R: pf, qf, lm, lsmeans, cld
SAS: GLM

Oct 28 PM: WB
Reading: si, si
Oct 31: WB, WB
Nov 2: WB, pdf, pdf
Nov 7-9
Unit 7. Experimental design
Blocking, covariates, unbalanced designes, lsmeans, mixed models, fixed and random effects, BLUPs and BLUEs

R: lme4, lmerTest, lmer, lsmeans, fixef, ranef, asreml
SAS: MIXED

Nov 7: WB,pdf, pdf
Optional: pdf
Nov 9
Unit 8. Non-parametric tests
Wilcox rank sum, Kolmogorov-Smirnov, Kruskal-Wallis, permutational ANOVA
R: wilcox, ks, kruskal, friedman, aovp Nov 9, AM: WB, pdf, pdf
Nov 9, PM: WB
Nov 14, 16
Fall Term Break No Classes
Nov 21-23
Unit 9. Regression and correlation analysis
Pearson correlation, linear regression, non-parametric regression, non-linear regression, bootstrapping
R: corr, lm, nls, AIC, boot
SAS: CORR, GML, NLIN
Nov 21: WB, pdf, pdf
Nov 23AM: WB, pdf, pdf
Nov 23
Unit 10. Tests for proportions
Chi-square test and z-test for proportions
R: prop, chisq, z.score

Nov 23PM: WB, pdf
Assignment 3: pdf, pdf
Nov 28
Guidlines for exam prep, course notes, and projects Project & assignment support. Opporunity for Q&A on all lecture topics Course notes guidelines: pdf
Nov 30
Project & assignment support AM & PM
Project & assignment support. Opporunity for Q&A on all lecture topics AM & PM
 
Dec 5
7:30am Start
RENR711: final presentations
(no class for RENR480)
Previous Projects
RENR 711 students: Final project due Dec 10, 11:59pm (deadline extended)
Guidelines: pdf
Dec 7
Final exam at 8am to 9:20am in classroom GSB866 RENR 480 students: Course notes due Dec 7, 8:00am (in classroom before exam)
Sample Questions: pdf


Fall 2016 Class Schedule


Date
Lectures Labs Download
Sep 1
Inroduction & course overview, linking statistics and science, scientific hypotheses   Syllabus:
Sep 1 AM: pps
Sep 1-8
Unit 1. Data management
Statistical vocabulary, data table concept, variable types, basic data management
Intro to R & SAS, data formatting and import, subset, merge, transform data
Sep 1 PM: pps,pdf, pdf
Sep 3: WB,pdf
Sep 8 AM: WB,pps
R Cheat Sheet: pdf
Sep 13
Unit 2. Exploratory graphics
Data checking, data cleaning, display of raw data
R: plot, boxplot, hist
SAS: HIST, GPLOT, BOXPLOT
Sep 10: pdf, pdf, WB
Reading: si
Sep 15-20
Unit 3. Descriptive statistics
Measures of spread, shape and central tencency, degrees of freedom, central limit theorem
R: aggregate, mean, sd, etc.
SAS: UNIVARIATE
Excel: Pivot tables
Sep 15, 20: WB, WB, WB
Sep 15: pdf, pdf
Assignment 1: pdf
Sep 22 - 29
Unit 4. Presentation of quantitative data
Scatter, line, bar, and dot plots, multi-panel plots, graphic customizations.
Scientific graphs in R
Sep 22 AM: WB, pdf, pdf
Sep 22 PM: pdf
Reading: si, si, si
Sep 27: pdf, pdf
Sep 29: pdf, pdf
Oct 4-6
Support sessions Projects, Labs, Assignments, Website
Assignment 2: pdf, pdf
Project guidelines: pdf, pps,pdf
Weebly 2016: pps
Oct 11-18
Unit 5. Principles of inferential statistics
SE, CI, T-Test, hypothesis testing

R: pnorm, qnorm, pt, qt, t.test, lm
SAS: TTEST, GLM

Oct 11, 13 AM: WB
Oct 13 PM: WB, pdf
Oct 18: WB, WB, WB
Reading: si, si
Oct 20 & Nov 1
Unit 6. Analysis of variance
One-way ANOVA, Two-way ANOVA, pairwise comparisons, assumptions, transformations

R: pf, qf, lm, lsmeans, cld
SAS: GLM

Oct 20AM: WB, pdf, pdf
Oct 20PM: WB, WB
Oct 25: WB, pdf, pdf
Reading: si, si

Oct 25
RENR711: project support
(no class for RENR480)
RENR711 project support
(no class for RENR480)
Presentation: link, link, link
Website: pps,pdf
Story telling: pps
Export graphics: pdf
Oct 27
RENR711: draft presentations
(no class for RENR480)
Previous Projects
Draft Project due Oct 27
Project Guidelines: pdf
Nov 1-3
Unit 7. Experimental design
Blocking, covariates, unbalanced designes, lsmeans, mixed models, fixed and random effects, BLUPs and BLUEs

R: lme4, lmerTest, lmer, lsmeans, fixef, ranef, asreml
SAS: MIXED

Nov 1: WB,pdf, pdf
Nov 3: pdf
Nov 3
Unit 8. Non-parametric tests
Wilcox rank sum, Kolmogorov-Smirnov, Kruskal-Wallis, permutational ANOVA
R: wilcox, ks, kruskal, friedman, aovp Nov 3, PM: WB, pdf, pdf
Method selection: WB
Nov 8, 10
Fall Term Break No Classes
Nov 15-17
Unit 9. Regression and correlation analysis
Pearson correlation, linear regression, non-parametric regression, non-linear regression, bootstrapping
R: corr, lm, nls, AIC, boot
SAS: CORR, GML, NLIN
Nov 15: WB, pdf, pdf
Nov 17AM: WB, pdf, pdf
Nov 17
Unit 10. Tests for proportions
Chi-square test and z-test for proportions
R: prop, chisq, z.score

Nov 17PM: WB, pdf
Assignment 3: pdf, pdf
Nov 22
Mini Lecture: Ordination
Mini Lecture: Guidlines for exam prep, course notes, and projects
Project & assignment support
Ordination: pdf, pdf
Nov 24
Project & assignment support AM & PM
Project & assignment support AM & PM
 
Nov 29
Review session
(taught by TAs, instructor abroad)
 
Dec 1
7:30am Start
RENR711: final presentations
(no class for RENR480)
Previous Projects
RENR 711 students: Final project due Dec 10 (deadline extended)
Guidelines: pdf
Dec 6
Final exam at 8am to 9:20am in classroom GSB866 RENR 480 students: Course notes due Dec 6 (8am in classroom)
Sample Questions: pdf


Fall 2015 Class Schedule


Date
Lectures Labs Download
Sep 1
Inroduction & course overview, linking statistics and science, scientific hypotheses   Syllabus:
Sep 1: pps
Sep 3-8
Unit 1. Data management
Statistical vocabulary, data table concept, variable types, basic data management
Intro to R & SAS, data formatting and import, subset, merge, transform data
Sep 3 AM: pps,pdf, pdf
Sep 3 PM: WB,pdf
Sep 8: WB,pps
R Cheat Sheet: pdf
Sep 10
Unit 2. Exploratory graphics
Data checking, data cleaning, display of raw data
R: plot, boxplot, hist
SAS: HIST, GPLOT, BOXPLOT
Sep 10: pdf, pdf, WB
Reading: si
Sep 15-17
Unit 3. Descriptive statistics
Measures of spread, shape and central tencency, degrees of freedom, central limit theorem
R: aggregate, mean, sd, etc.
SAS: UNIVARIATE
Excel: Pivot tables
Sep 15, 17: WB, WB, WB
Sep 17: pdf, pdf
Assignment 1: pdf
Sep 23 - Oct 1
Unit 4. Presentation of quantitative data
Scatter, line, bar, and dot plots, multi-panel plots, graphic customizations.
Scientific graphs in R
Sep 22: WB, pdf, pdf
Sep 24: pdf
Reading: si, si, si
Sep 29: pdf, pdf
Oct 1: pdf, pdf
Assignment 2: pdf, pdf
Oct 6-15
Unit 5. Principles of inferential statistics
SE, CI, T-Test, hypothesis testing

R: pnorm, qnorm, pt, qt, t.test, lm
SAS: TTEST, GLM

Oct 6: WB
Oct 8: WB, pdf
Oct 13: WB
Oct 15: WB
Oct 15-22
Unit 6. Analysis of variance
One-way and two-way ANOVA, assumptions, transformations

R: pf, qf, lm, shapiro, bartlett
SAS: GLM

Oct 15: WB, pdf
Oct 20: WB, WB
Oct 22: WB, pdf
Oct 27
Course project support Course project support
Presentation: link, link, link
Website: pps,pdf
Story telling: pps
Export graphics: pdf
Oct 29
Course project presentations Previous Projects
Draft Project due Oct 29
Project Guidelines: pdf
Nov 3
Unit 7. Experimental design
Common experimental designs, blocking, covariates, mixed models

R: lme4, multcomp
SAS: MIXED

Oct 31: WB,pdf, pdf
Nov 5
Unit 8. Non-parametric tests
Wilcox rank sum, Kolmogorov-Smirnov, Kruskal-Wallis, permutational ANOVA
R: wilcox, ks, kruskal, friedman, adonis
SAS: NPAR1WAY
Nov 5am: WB, pdf, pdf
Nov 5pm: WB, pdf, pdf
Method selection: WB
Assignment 3: pdf
Nov 9-13
Fall Term Break No Classes
Nov 17-19
Unit 9. Regression and correlation analysis
Pearson correlation, linear regression, non-parametric regression, non-linear regression, bootstrapping
R: corr, lm, nls, AIC, boot
SAS: CORR, GML, NLIN
Nov 17: WB, pdf, pdf
Nov 19: WB, pdf, pdf
Nov 24
Unit 10. Tests for proportions
Chi-square test and z-test for proportions
R: prop, chisq, z.score

Nov 24: WB, pdf
Nov 26
Review sessions AM & PM
Course project support AM & PM
 
Dec 1
Course project presentations Previous Projects
RENR 711 students: Final project due Dec 8 (deadline extended)
Guidelines: pdf
Dec 3
Final exam at 8am to 9:20am in classroom GSB866 RENR 480 students: Course notes due Dec 3 (8am in classroom)
Sample Questions: pdf


Fall 2013 Class Schedule


Date
Lectures Labs Download
Sep 5
Inroduction & course overview, linking statistics and science, scientific hypotheses   Syllabus:
Sep 5: pps
Sep 9-12
Unit 1. Data management
Statistical vocabulary, data table concept, variable types, basic data management
Intro to R & SAS, data formatting and import, subset, merge, transform data
Sep 9: pps,pdf, pdf
Sep 10: WB,pdf
Sep 12: WB,pps
R Cheat Sheet: pdf
Sep 16
Unit 2. Exploratory graphics
Data checking, data cleaning, display of raw data
R: plot, boxplot, hist
SAS: HIST, GPLOT, BOXPLOT
Sep 16: pdf, pdf, WB
Reading: si
Sep 17-23
Unit 3. Descriptive statistics
Measures of spread, shape and central tencency, degrees of freedom, central limit theorem
R: aggregate, mean, sd, etc.
SAS: UNIVARIATE
Excel: Pivot tables
Sep 17: pps
Sep 19: pdf, pdf
Assignment 1:pdf
Sep 23: WB, WB, WB
Sep 23 - 30
Unit 4. Presentation of quantitative data
Scatter, line, bar, and dot plots, multi-panel plots, graphic customizations.
Scientific graphs in R
Sep 23: WB, pdf, pdf
Sep 24: pdf
Reading: si, si, si
Sep 26: pdf, pdf
Sep 30: pdf, pdf
Assignment 2: pdf, pdf
Oct 1-7
Unit 5. Principles of inferential statistics
SE, CI, T-Test, hypothesis testing

R: pnorm, qnorm, pt, qt, t.test, lm
SAS: TTEST, GLM

Oct 1: WB
Oct 3: WB, pdf
Oct 7: WB, WB
Oct 8-15
Unit 6. Analysis of variance
One-way and two-way ANOVA, assumptions, transformations

R: pf, qf, lm, shapiro, bartlett
SAS: GLM

Oct 8: WB, pdf
Oct 10, 15: WB, WB
Oct 15, 17: WB, pdf
Oct 21-24
Course project support Course project support
Presentation: link, link, link
Website: pps,pdf
Story telling: pps
Export graphics: pdf
Oct 28
Course project presentations Previous Projects
Draft Project due Oct 28
Project Guidelines: pdf
Oct 31
Unit 7. Experimental design
Common experimental designs, blocking, covariates, mixed models

R: lme4, multcomp
SAS: MIXED

Oct 31: WB,pdf, pdf
Nov 4
Unit 8. Non-parametric tests
Wilcox rank sum, Kolmogorov-Smirnov, Kruskal-Wallis, permutational ANOVA
R: wilcox, ks, kruskal, friedman, adonis
SAS: NPAR1WAY
Nov 4: WB, pdf, pdf
Nov 4: WB, pdf, pdf
Method selection: WB
Assignment 3: pdf
Nov 5-7
Unit 9. Regression and correlation analysis
Pearson correlation, linear regression, non-parametric regression, non-linear regression, bootstrapping
R: corr, lm, nls, AIC, boot
SAS: CORR, GML, NLIN
Nov 5: WB, pdf, pdf
Nov 7: WB, pdf, pdf
Nov 12-13
Fall Term Break No Classes
Nov 14
Unit 10. Tests for proportions
Chi-square test and z-test for proportions
R: prop, chisq, z.score

Nov 14: WB, pdf
Nov 18-22
Topics by request
Course project support
 
Nov 25-26
Course project presentations Previous Projects
Final Project due Nov 25
Guidelines: pdf
Nov 28 - Dec 2
Review Sessions

 
Dec 4
Final Exam on last day of classes in classroom Hard deadline for late assignments, notes, and projects Dec 4
Sample Questions: pdf


Fall 2012 Class Schedule


Date
Lectures Labs Download
Sep 6
Inroduction & course overview, linking statistics and science, scientific hypotheses   Syllabus:
Reading: si
Sep 6: pps
Sep 10-13
Unit 1. Data management
Statistical vocabulary, data table concept, variable types, basic data management
Intro to R & SAS, data formatting and import, subset, merge, transform data
Sep 10: pps,pdf, pdf
Sep 11: WB,pdf
Sep 13: WB,pps
Sep 16
Unit 2. Exploratory graphics
Data checking, data cleaning, display of raw data
R: plot, boxplot, hist
SAS: HIST, GPLOT, BOXPLOT
Sep 16: pdf, pdf, WB
Reading: si
Sep 18-25
Unit 3. Descriptive statistics
Measures of spread, shape and central tencency, degrees of freedom, central limit theorem
R: aggregate, mean, sd, etc.
SAS: UNIVARIATE
Excel: Pivot tables
Sep 18: WB
Sep 20: WB, WB
Sep 24: pdf, pdf
Sep 25:link
Assignment 1:pdf
Sep 27 - Oct 2
Unit 4. Presentation of quantitative data
Scatter, line, bar, and dot plots, multi-panel plots, graphic customizations.
Scientific graphs in R
Sep 27: WB, pdf, pdf
Oct 1: pdf, pdf, pdf
Reading: si, si, si
Oct 2: pdf, pdf
Reading: si, si
Assignment 2: pdf, pdf
Oct 4-11
  Course project support
Project Guidelines: pdf
Presentation: link, link, link
Oct 4: pps,pdf
Oct 9: pps
Oct 11: pdf
Oct 15-18
Unit 5. Principles of parametric statistics
SE, CI, T-Test, hypothesis testing

R: pnorm, qnorm, pt, qt, t.test, lm
SAS: TTEST, GLM

Oct 15: WB
Oct 16: WB, pdf
Oct 18: WB
Recap: WB
Oct 22-29
Unit 6. Analysis of variance
One-way and two-way ANOVA, assumptions, transformations

R: pf, qf, lm, shapiro, bartlett
SAS: GLM

Oct 22: WB, pdf
Oct 23: WB
Oct 25: WB
Oct 29: pdf
Oct 30 -
Nov 1
Course project support
Assignment 3: pdf, pdf
Ignite talks: pdf
Nov 5
Course project presentations Draft Projects
Draft Project due Nov 5
Guidelines: pdf,pps
Nov 8
Unit 7. Experimental design
Common experimental designs, blocking, covariates, mixed models


Nov 8: pps
Nov 27: WB,pdf, pdf
Nov 15-19
Unit 8. Non-parametric tests
Wilcox rank sum, Kolmogorov-Smirnov, Kruskal-Wallis, permutational ANOVA
R: wilcox, ks, kruskal, friedman, adonis
SAS: NPAR1WAY
FORTRAN: permanova6
Nov 15: WB, pdf
Nov 19: WB, pps, pdf, pdf
standard ANOVA: pdf
permutational ANOVA: pdf
Nov 20-26
Unit 9. Regression and correlation analysis
Pearson correlation, linear regression, non-parametric regression, non-linear regression, bootstrapping
R: corr, lm, nls, AIC, boot
SAS: CORR, GML, NLIN
Nov 20: WB, pdf, pdf
Nov 22-26: WB, pdf, pdf
Nov 26
Unit 10. Tests for proportions
Chi-square test and z-test for proportions
R: prop, chisq, z.score

Nov 26: WB, pdf
Nov 27-29
Various Topics, Review
Course project support
Assignment 4: pdf, pdf
Ordination: pdf, pdf
Dec 3
Course project presentations Previous Projects
Final Project due Dec 6
Guidelines: pdf
Dec 4
Final Exam on last day of classes in classroom Hard deadline for late assignments, notes, and projects Dec 6
Sample Questions: pdf


Fall 2010 Class Schedule


Date
Lectures Labs Download
Sep 9
Inroduction & course overview, linking statistics and science, scientific hypotheses   Syllabus:
Reading: si
Sep 13-16
Unit 1. Data management
Basic statistical vocabulary, data table concept, data management
Intro to R & SAS, data formatting and import, subset, merge, transform data
Sep 13: pps,pdf
Sep 14: WB,pdf,pps
Sep 16: WB
Sep 20
Unit 2. Exploratory graphics
Data checking, data cleaning, display of raw data
R: plot, boxplot, hist
SAS: HIST, GPLOT, BOXPLOT
Sep 21: pdf, pdf, WB
Sep 21-27
Unit 3. Descriptive statistics
Measures of spread, shape and central tencency, variable types, degrees of freedom
R: aggregate, mean, sd, etc.
SAS: UNIVARIATE
Excel: Pivot tables
Sep 21: WB
Sep 23: WB,pdf
Oct 4: WB
Assignment 1: pdf
Sep 27 - Oct 4
Unit 4. Presentation of quantitative data
Scatter plots, multi-panel, line, bar, dot, combinations.
Scientific graphs in R
Labs: pdf,pdf,pdf,pdf,pdf
Lectures: WB
Cheat sheets: pdf,pdf,WB
Assignment 2: pdf, pdf
Oct 4
  Course project support
Project: pdf,pps,pdf
Oct 5-12
Unit 5. Principles of parametric statistics
SE, CI, T-Test, hypothesis testing

R: pnorm, qnorm, pt, qt, t.test, lm
SAS: TTEST, GLM

Lecture: WB
Lab: pdf
Oct 13-25
Unit 6. Analysis of variance
One-way and two-way ANOVA, assumptions, transformations

R: pf, qf, lm, shapiro, bartlett
SAS: GLM

Lectures: WB,WB,WB
Lab: pdf,pdf
Oct 26
Unit 7. Non-parametric tests
Wilcox rank sum, Kolmogorov-Smirnov, Kruskal-Wallis
R: wilcox, ks, kruskal, friedman
SAS: NPAR1WAY
Lecture: WB
Lab: pdf
Oct 28
Unit 8. Tests for proportions
Chi-square test and z-test for proportions
R: prop, chisq, z.score

Lecture: WB
Lab: pdf
Nov 1-4
Course project support
Assignment 3: pdf, pdf
Nov 8
Course project presentations Previous Projects
Draft Project due Nov 8
Guidelines: pdf,pps
Nov 9
Unit 9. Simple linear regression
Pearson correlation, linear regression, assumptions, multiple inference
R: corr, lm
SAS: CORR, GML
Lecture:WB
Lab:pdf, pdf
Nov 15
Unit 10. The general linear model
multiple linear regression, Blocking, regression approach to ANOVA, ANOCOVA, blocking, mixed models
R: lm, lmer
SAS: GML, MIXED
Lecture: WB
Lab: pdf, pdf
Nov 12-16
Unit 11. Non-linear regression
Curve fitting and Akaike's Information Criterium (AIC)
R: nls, AIC
SAS: NLIN
Lecture:WB
Lab:pdf, pdf
Nov 18
Unit 12. permutational ANOVA
A new analysis of variance approach for non-normal data
FORTRAN: permanova6 (balanced, uni & multivar)
R: adonis (unbalanced, multivar)
Lecture: WB, pps
Lab: pdf, pdf
standard ANOVA: pdf
permutational ANOVA: pdf
Nov 22 - Dec 2
Various Topics
Course project support
Assignment 4: pdf, pdf
Ordination: pdf, pdf Bootstrapping: pdf, pdf
Dec 6
Course project presentations Previous Projects
Final Project due Dec 6
Guidelines: pdf
Dec 7
Final Exam on last day of classes in classroom Hard deadline for late assignments, notes, and projects Dec 7
Sample Questions: pdf