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: 

Sep 613 
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: , Sep 11: ,, Sep 13: , , , , R Cheat Sheet: 
Sep 19 
Unit 2. Exploratory graphics Data checking, data cleaning, display of raw data, diagnostic plots 
R: plot, pairs, sunflowerplot, boxplot, hist 
Sep 18: , , Reading: 
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: , Sep 20 Lab: , Sep 25: Assignment 1: , 
Sep 27  Oct 4 
Unit 4. Presentation of quantitative data Scatter, line, bar, and dot plots, multipanel plots, graphic customizations. 
Scientific graphs in R 
Sep 27 AM: , , , Sep 27 PM: , , Oct 2: , , Oct 4 AM: , , 
Oct 4 
Support session  Projects, Labs, Assignments, Website 
Graphics touchup: Project guidelines: , Website, Weebly: , Assignment 2: , 
Oct 918 
Unit 5. Principles of inferential statistics SE, CI, TTest, Hypothesis testing 
R: pnorm, qnorm, pt, qt, t.test 
Oct 9, 11 AM: Oct 11 PM: , Oct 16: Oct 18 AM: Reading: , 
Oct 18 
Unit 6. Analysis of variance Oneway ANOVA, pairwise comparisons 
R: pf, qf, lm, lsmeans, cld 
Oct 18 PM: , , 
Oct 23 
RENR711: project support (no class for RENR480) 
RENR711 project support (no class for RENR480) 
Presentation: , , Website: , Export graphics: 
Oct 26 
RENR711: draft presentations (no class for RENR480) 
Previous Projects Draft website due Oct 28, 23:59 
Project Guidelines: 
Oct 20 & Nov 1 
Unit 6. continued Twoway ANOVA, assumptions, transformations 
R: pf, qf, lm, lsmeans, cld 
Oct 30: Reading: , Nov 1 AM: , Nov 1 PM: , , 
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: ,, Optional: 
Nov 8 
Unit 8. Nonparametric tests Wilcox rank sum, KolmogorovSmirnov, KruskalWallis, permutational ANOVA 
R: wilcox, ks, kruskal, friedman, aovp  Nov 8, AM: , , Nov 8, PM: 
Nov 13, 15 
Fall Term Break  No Classes  
Nov 2022 
Unit 9. Regression and correlation analysis Pearson correlation, linear regression, nonparametric regression, nonlinear regression, bootstrapping 
R: corr, lm, nls, AIC, boot 
Nov 20: , , Assignment 3: , Nov 22AM: , , 
Nov 22 
Unit 10. Tests for proportions Chisquare test and ztest for proportions 
R: prop, chisq, z.score 
Nov 22PM: , 
Nov 27 
Guidlines for exam prep, course notes, and projects  Project & assignment support. Opporunity for Q&A on all lecture topics  Course notes guidelines: Overview of techniques: 
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: 
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: 
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: 

Sep 613 
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: , Sep 12: , Sep 15: , R Cheat Sheet: 
Sep 19 
Unit 2. Exploratory graphics Data checking, data cleaning, display of raw data 
R: plot, boxplot, hist SAS: HIST, GPLOT, BOXPLOT 
Sep 19: , , Reading: 
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 2125: , , Sep 21: , Assignment 1: 
Sep 28  Oct 5 
Unit 4. Presentation of quantitative data Scatter, line, bar, and dot plots, multipanel plots, graphic customizations. 
Scientific graphs in R 
Sep 28 AM: , , Sep 28 PM: Oct 3: , Oct 5 AM: , Reading: , , 
Oct 5 
Support session  Projects, Labs, Assignments, Website 
Assignment 2: , Project guidelines: , , Weebly 2016: 
Oct 1019 
Unit 5. Principles of inferential statistics SE, CI, TTest 
R: pnorm, qnorm, pt, qt, t.test, lm 
Oct 10, 12 AM: Oct 12 PM: , Oct 17, 19: , Reading: , 
Oct 19 
Unit 6. Analysis of variance Oneway ANOVA 
R: pf, qf, lm, 
Oct 19 AM: , , 
Oct 24 
RENR711: project support (no class for RENR480) 
RENR711 project support (no class for RENR480) 
Presentation: , , Website: , Export graphics: 
Oct 26 
RENR711: draft presentations (no class for RENR480) 
Previous Projects Draft Project due Oct 26 
Project Guidelines: 
Oct 20 & Nov 1 
Unit 6. continued Twoway ANOVA, assumptions, transformations 
R: pf, qf, lm, lsmeans, cld 
Oct 28 PM: Reading: , Oct 31: , Nov 2: , , 
Nov 79 
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 7: ,, Optional: 
Nov 9 
Unit 8. Nonparametric tests Wilcox rank sum, KolmogorovSmirnov, KruskalWallis, permutational ANOVA 
R: wilcox, ks, kruskal, friedman, aovp  Nov 9, AM: , , Nov 9, PM: 
Nov 14, 16 
Fall Term Break  No Classes  
Nov 2123 
Unit 9. Regression and correlation analysis Pearson correlation, linear regression, nonparametric regression, nonlinear regression, bootstrapping 
R: corr, lm, nls, AIC, boot SAS: CORR, GML, NLIN 
Nov 21: , , Nov 23AM: , , 
Nov 23 
Unit 10. Tests for proportions Chisquare test and ztest for proportions 
R: prop, chisq, z.score 
Nov 23PM: , Assignment 3: , 
Nov 28 
Guidlines for exam prep, course notes, and projects  Project & assignment support. Opporunity for Q&A on all lecture topics  Course notes guidelines: 
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: 
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: 
Date 
Lectures  Labs  Download 

Sep 1 
Inroduction & course overview, linking statistics and science, scientific hypotheses  Syllabus: Sep 1 AM: 

Sep 18 
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: ,,
Sep 3: , Sep 8 AM: , R Cheat Sheet: 
Sep 13 
Unit 2. Exploratory graphics Data checking, data cleaning, display of raw data 
R: plot, boxplot, hist SAS: HIST, GPLOT, BOXPLOT 
Sep 10: , , Reading: 
Sep 1520 
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: , , Sep 15: , Assignment 1: 
Sep 22  29 
Unit 4. Presentation of quantitative data Scatter, line, bar, and dot plots, multipanel plots, graphic customizations. 
Scientific graphs in R 
Sep 22 AM: , , Sep 22 PM: Reading: , , Sep 27: , Sep 29: , 
Oct 46 
Support sessions  Projects, Labs, Assignments, Website 
Assignment 2: , Project guidelines: , , Weebly 2016: 
Oct 1118 
Unit 5. Principles of inferential statistics SE, CI, TTest, hypothesis testing 
R: pnorm, qnorm, pt, qt, t.test, lm 
Oct 11, 13 AM: Oct 13 PM: , Oct 18: , , Reading: , 
Oct 20 & Nov 1 
Unit 6. Analysis of variance Oneway ANOVA, Twoway ANOVA, pairwise comparisons, assumptions, transformations 
R: pf, qf, lm, lsmeans, cld 

Oct 25 
RENR711: project support (no class for RENR480) 
RENR711 project support (no class for RENR480) 
Presentation: , , Website: , Story telling: Export graphics: 
Oct 27 
RENR711: draft presentations (no class for RENR480) 
Previous Projects Draft Project due Oct 27 
Project Guidelines: 
Nov 13 
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 1: ,, Nov 3: 
Nov 3 
Unit 8. Nonparametric tests Wilcox rank sum, KolmogorovSmirnov, KruskalWallis, permutational ANOVA 
R: wilcox, ks, kruskal, friedman, aovp  Nov 3, PM: , , Method selection: 
Nov 8, 10 
Fall Term Break  No Classes  
Nov 1517 
Unit 9. Regression and correlation analysis Pearson correlation, linear regression, nonparametric regression, nonlinear regression, bootstrapping 
R: corr, lm, nls, AIC, boot SAS: CORR, GML, NLIN 
Nov 15: , , Nov 17AM: , , 
Nov 17 
Unit 10. Tests for proportions Chisquare test and ztest for proportions 
R: prop, chisq, z.score 
Nov 17PM: , Assignment 3: , 
Nov 22 
Mini Lecture: Ordination Mini Lecture: Guidlines for exam prep, course notes, and projects 
Project & assignment support 
Ordination: , 
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: 
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: 
Date 
Lectures  Labs  Download 

Sep 1 
Inroduction & course overview, linking statistics and science, scientific hypotheses  Syllabus: Sep 1: 

Sep 38 
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: ,,
Sep 3 PM: , Sep 8: , R Cheat Sheet: 
Sep 10 
Unit 2. Exploratory graphics Data checking, data cleaning, display of raw data 
R: plot, boxplot, hist SAS: HIST, GPLOT, BOXPLOT 
Sep 10: , , Reading: 
Sep 1517 
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: , , Sep 17: , Assignment 1: 
Sep 23  Oct 1 
Unit 4. Presentation of quantitative data Scatter, line, bar, and dot plots, multipanel plots, graphic customizations. 
Scientific graphs in R 
Sep 22: , , Sep 24: Reading: , , Sep 29: , Oct 1: , Assignment 2: , 
Oct 615 
Unit 5. Principles of inferential statistics SE, CI, TTest, hypothesis testing 
R: pnorm, qnorm, pt, qt, t.test, lm 
Oct 6: Oct 8: , Oct 13: Oct 15: 
Oct 1522 
Unit 6. Analysis of variance Oneway and twoway ANOVA, assumptions, transformations 
R: pf, qf, lm, shapiro, bartlett 
Oct 15: , Oct 20: , Oct 22: , 
Oct 27 
Course project support  Course project support 
Presentation: , , Website: , Story telling: Export graphics: 
Oct 29 
Course project presentations  Previous Projects Draft Project due Oct 29 
Project Guidelines: 
Nov 3 
Unit 7. Experimental design Common experimental designs, blocking, covariates, mixed models 
R: lme4, multcomp 
Oct 31: ,, 
Nov 5 
Unit 8. Nonparametric tests Wilcox rank sum, KolmogorovSmirnov, KruskalWallis, permutational ANOVA 
R: wilcox, ks, kruskal, friedman, adonis SAS: NPAR1WAY 
Nov 5am: , , Nov 5pm: , , Method selection: Assignment 3: 
Nov 913 
Fall Term Break  No Classes  
Nov 1719 
Unit 9. Regression and correlation analysis Pearson correlation, linear regression, nonparametric regression, nonlinear regression, bootstrapping 
R: corr, lm, nls, AIC, boot SAS: CORR, GML, NLIN 
Nov 17: , , Nov 19: , , 
Nov 24 
Unit 10. Tests for proportions Chisquare test and ztest for proportions 
R: prop, chisq, z.score 
Nov 24: , 
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: 
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: 
Date 
Lectures  Labs  Download 

Sep 5 
Inroduction & course overview, linking statistics and science, scientific hypotheses  Syllabus: Sep 5: 

Sep 912 
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: ,,
Sep 10: , Sep 12: , R Cheat Sheet: 
Sep 16 
Unit 2. Exploratory graphics Data checking, data cleaning, display of raw data 
R: plot, boxplot, hist SAS: HIST, GPLOT, BOXPLOT 
Sep 16: , , Reading: 
Sep 1723 
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: Sep 19: , Assignment 1: Sep 23: , , 
Sep 23  30 
Unit 4. Presentation of quantitative data Scatter, line, bar, and dot plots, multipanel plots, graphic customizations. 
Scientific graphs in R 
Sep 23: , , Sep 24: Reading: , , Sep 26: , Sep 30: , Assignment 2: , 
Oct 17 
Unit 5. Principles of inferential statistics SE, CI, TTest, hypothesis testing 
R: pnorm, qnorm, pt, qt, t.test, lm 
Oct 1: Oct 3: , Oct 7: , 
Oct 815 
Unit 6. Analysis of variance Oneway and twoway ANOVA, assumptions, transformations 
R: pf, qf, lm, shapiro, bartlett 
Oct 8: , Oct 10, 15: , Oct 15, 17: , 
Oct 2124 
Course project support  Course project support 
Presentation: , , Website: , Story telling: Export graphics: 
Oct 28 
Course project presentations  Previous Projects Draft Project due Oct 28 
Project Guidelines: 
Oct 31 
Unit 7. Experimental design Common experimental designs, blocking, covariates, mixed models 
R: lme4, multcomp 
Oct 31: ,, 
Nov 4 
Unit 8. Nonparametric tests Wilcox rank sum, KolmogorovSmirnov, KruskalWallis, permutational ANOVA 
R: wilcox, ks, kruskal, friedman, adonis SAS: NPAR1WAY 
Nov 4: , , Nov 4: , , Method selection: Assignment 3: 
Nov 57 
Unit 9. Regression and correlation analysis Pearson correlation, linear regression, nonparametric regression, nonlinear regression, bootstrapping 
R: corr, lm, nls, AIC, boot SAS: CORR, GML, NLIN 
Nov 5: , , Nov 7: , , 
Nov 1213 
Fall Term Break  No Classes  
Nov 14 
Unit 10. Tests for proportions Chisquare test and ztest for proportions 
R: prop, chisq, z.score 
Nov 14: , 
Nov 1822 
Topics by request 
Course project support 

Nov 2526 
Course project presentations  Previous Projects Final Project due Nov 25 
Guidelines: 
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: 
Date 
Lectures  Labs  Download 

Sep 6 
Inroduction & course overview, linking statistics and science, scientific hypotheses  Syllabus: Reading: Sep 6: 

Sep 1013 
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: ,, Sep 11: , Sep 13: , 
Sep 16 
Unit 2. Exploratory graphics Data checking, data cleaning, display of raw data 
R: plot, boxplot, hist SAS: HIST, GPLOT, BOXPLOT 
Sep 16: , , Reading: 
Sep 1825 
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: Sep 20: , Sep 24: , Sep 25: Assignment 1: 
Sep 27  Oct 2 
Unit 4. Presentation of quantitative data Scatter, line, bar, and dot plots, multipanel plots, graphic customizations. 
Scientific graphs in R 
Sep 27: , , Oct 1: , , Reading: , , Oct 2: , Reading: , Assignment 2: , 
Oct 411 
Course project support 
Project Guidelines: Presentation: , , Oct 4: , Oct 9: Oct 11: 

Oct 1518 
Unit 5. Principles of parametric statistics SE, CI, TTest, hypothesis testing 
R: pnorm, qnorm, pt, qt, t.test, lm 
Oct 15: Oct 16: , Oct 18: Recap: 
Oct 2229 
Unit 6. Analysis of variance Oneway and twoway ANOVA, assumptions, transformations 
R: pf, qf, lm, shapiro, bartlett 
Oct 22: , Oct 23: Oct 25: Oct 29: 
Oct 30  Nov 1 
Course project support 
Assignment 3: , Ignite talks: 

Nov 5 
Course project presentations  Draft Projects Draft Project due Nov 5 
Guidelines: , 
Nov 8 
Unit 7. Experimental design Common experimental designs, blocking, covariates, mixed models 

Nov 8: Nov 27: ,, 
Nov 1519 
Unit 8. Nonparametric tests Wilcox rank sum, KolmogorovSmirnov, KruskalWallis, permutational ANOVA 
R: wilcox, ks, kruskal, friedman, adonis SAS: NPAR1WAY FORTRAN: permanova6 
Nov 15: , Nov 19: , , , standard ANOVA: permutational ANOVA: 
Nov 2026 
Unit 9. Regression and correlation analysis Pearson correlation, linear regression, nonparametric regression, nonlinear regression, bootstrapping 
R: corr, lm, nls, AIC, boot SAS: CORR, GML, NLIN 
Nov 20: , , Nov 2226: , , 
Nov 26 
Unit 10. Tests for proportions Chisquare test and ztest for proportions 
R: prop, chisq, z.score 
Nov 26: , 
Nov 2729 
Various Topics, Review 
Course project support 
Assignment 4: , Ordination: , 
Dec 3 
Course project presentations  Previous Projects Final Project due Dec 6 
Guidelines: 
Dec 4 
Final Exam on last day of classes in classroom  Hard deadline for late assignments, notes, and projects Dec 6

Sample Questions: 
Date 
Lectures  Labs  Download 

Sep 9 
Inroduction & course overview, linking statistics and science, scientific hypotheses  Syllabus: Reading: 

Sep 1316 
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: , Sep 14: ,, Sep 16: 
Sep 20 
Unit 2. Exploratory graphics Data checking, data cleaning, display of raw data 
R: plot, boxplot, hist SAS: HIST, GPLOT, BOXPLOT 
Sep 21: , , 
Sep 2127 
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: Sep 23: , Oct 4: Assignment 1: 
Sep 27  Oct 4 
Unit 4. Presentation of quantitative data Scatter plots, multipanel, line, bar, dot, combinations. 
Scientific graphs in R 
Labs: ,,,, Lectures: Cheat sheets: ,, Assignment 2: , 
Oct 4 
Course project support 
Project: ,,  
Oct 512 
Unit 5. Principles of parametric statistics SE, CI, TTest, hypothesis testing 
R: pnorm, qnorm, pt, qt, t.test, lm 
Lecture: Lab: 
Oct 1325 
Unit 6. Analysis of variance Oneway and twoway ANOVA, assumptions, transformations 
R: pf, qf, lm, shapiro, bartlett 
Lectures: ,, Lab: , 
Oct 26 
Unit 7. Nonparametric tests Wilcox rank sum, KolmogorovSmirnov, KruskalWallis 
R: wilcox, ks, kruskal, friedman SAS: NPAR1WAY 
Lecture: Lab: 
Oct 28 
Unit 8. Tests for proportions Chisquare test and ztest for proportions 
R: prop, chisq, z.score 
Lecture: Lab: 
Nov 14 
Course project support  Assignment 3: ,  
Nov 8 
Course project presentations  Previous Projects Draft Project due Nov 8 
Guidelines: , 
Nov 9 
Unit 9. Simple linear regression Pearson correlation, linear regression, assumptions, multiple inference 
R: corr, lm SAS: CORR, GML 
Lecture: Lab:, 
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: Lab: , 
Nov 1216 
Unit 11. Nonlinear regression Curve fitting and Akaike's Information Criterium (AIC) 
R: nls, AIC SAS: NLIN 
Lecture: Lab:, 
Nov 18 
Unit 12. permutational ANOVA A new analysis of variance approach for nonnormal data 
FORTRAN: permanova6 (balanced, uni & multivar) R: adonis (unbalanced, multivar) 
Lecture: , Lab: , standard ANOVA: permutational ANOVA: 
Nov 22  Dec 2 
Various Topics 
Course project support 
Assignment 4: , Ordination: , Bootstrapping: , 
Dec 6 
Course project presentations  Previous Projects Final Project due Dec 6 
Guidelines: 
Dec 7 
Final Exam on last day of classes in classroom  Hard deadline for late assignments, notes, and projects Dec 7

Sample Questions: 