| Lecture number | Recording
Date |
Topics | Reading | Assignments | Computer material |
| 1 | 5/14 | Introduction, grading policies, review | |||
| 2 | 5/14 | Introduction to R, SAS and other software options | R,
SAS Exercise SAS solution R solution Python solution |
burgers,
student.csv, intro SAS file, SAS output, R intro code |
|
| 3 | 5/15 | Continued review of introductory statistics | |||
| 4a, b, c | 5/15 | Review; linear regression | Ott, sections 11.1-11.4 | review
probs 1 SAS program SAS Output R code |
cereal
data, cereal SAS file, SAS output, R cereal code Python code |
| 5 | 5/16 | Simple linear Regression | Ott, 11.1-11.4 | salary
data, salary SAS file, SAS output, R salary code Python code |
|
| 6 | 5/16 | Review | rev
1 solutions, chicken data, sticker data |
||
| 7a,b | 5/17 | Linear regression topics; Correlation | Ott 11.5 - 11.7 | grasshopper
SAS file, SAS output, R grasshopper code Python code |
|
| 5/17 | Exam 1 (due by February 9) | ||||
| EA1, 8 | 5/21 | Linear regression topics; Correlation | Ott 11.5 - 11.7 | review
probs 2 SAS program SAS Output Some R code |
|
| 9 a, b | 5/21 | Matrix- based approach | Ott 12.9 | ||
| 10a, b | 5/22 | Multiple regression | Ott, 12.1-12.4 | salary
SAS file2, SAS output, R salary2 code subs SAS file, SAS output, R subs code Python code |
|
| 11 | 5/22 | Multiple regression | Ott, 12.1-12.5 | ||
| 12a, b | 5/23 | Multiple regression | Ott, 12.5-12.7 | SAS TestSubset, SAS output |
|
| 13 | 5/23 | Review | rev 2 solutions | ||
| 14 | 5/24 | Multiple regression | Ott, 12.5-12.8 | logistic SAS file, SAS output, R logistic code, Python code |
|
| 5/24 | Exam 2 (due by March 6) | ||||
| EA2, 15 | 5/29 | Multiple regression/ Building regression models |
Ott, 12.5-12.8/ 13.1-13.4 |
project description
due, review probs 3 SAS program SAS Output |
autos.txt, autos SAS file1, SAS output, R autos1 code |
| 16 | 5/29 | Building regression models | Ott, 13.1-13.4 | autos SAS file2, SAS output, R autos2 code |
|
| 17 | 5/30 | Building regression models | Ott, 13.1-13.4 | model
fitting data, modeling SAS file, SAS output, R modeling code |
|
| 18 | 5/30 | Review | rev 3 solutions, 12.12 data, 12.53 data, 13.3 data, |
||
| 19 | 5/31 | ANOVA CR-p design | Ott, 8.1-8.4 | cuckoo data, cuckoo SAS file, SAS output, R cuckoo code Python code |
|
| 5/31 | Exam 3 (due by March 6) | ||||
| EA3, 20a, b | 6/4 | ANOVA CR-p design | Ott, 8.3-8.5 | review probs 4, SAS program, SAS output |
|
| 21 | 6/4 | ANOVA CR-p design; Multiple Comparisons |
Ott, 8.5-8.6, 9.1 | KW SAS file, SAS output, R KW code, Python code |
|
| 22 | 6/5 | Multiple Comparisons | Ott, 9.1-9.5 | ||
| 23 a, b | 6/5 | Multiple Comparisons, General Linear Model approach to ANOVA |
Ott, 9.4, 9.5, 9.9 | GLM SAS file, SAS output, R GLM code |
|
| 24 | 6/6 | Overview of experimental designs, Factorial Treatment Structure |
Ott, 14.1-14.3 | hot dog data, CRF SAS file, SAS output, R CRF code, Python code |
|
| 25 | 6/6 | Review | rev 4 solutions, ex13.52 data, ex13.67 data, ex8.7 data, ex8.29 data |
||
| 26 | 6/7 | Factorial Treatment Structure, Multiple Comparisons |
Ott, 14.3, 14.5 | CRF SAS file2, SAS output, R CRF code |
|
| 6/7 | Exam 4 (due by April 17) | ||||
| EA4, 27 | 6/11 | Randomized Block Design | Ott, 15.1-15.2 | review probs 5, SAS program, SAS output |
allergy data, RCB SAS file, SAS output, R RCB code, Python code |
| 28 | 6/11 | R B Design/ Latin Square Design | Ott, 15.2-15.3 | car data, Latin square SAS file, SAS output, R Latin square code Python code |
|
| 29 | 6/12 | Unbalanced data | Ott, 14.4 | unbalanced data unbalanced SAS file, SAS output, R unbalanced code |
|
| 30 a,b | 6/12 | Power and Sample Size | Ott, 14.6 | Power SAS file, SAS output, R power code |
|
| 31 | 6/13 | Rand. Block Factorial Expt., Multiple Comparisons |
Ott, 15.4 | RBF SAS file, SAS output, R RBF code |
|
| 32 | 6/13 | Review | rev 5 solutions | ||
| 33 | 6/14 | Friedman's test | Ott, 15.5 | Friedman SAS file, SAS output, R Friedman code |
|
| 6/14 | Exam 5 (due by April 17) | ||||
| EA5, 34 | 6/18 | Back to GLM approach to ANOVA; Analysis of covariance |
Ott, 12.9, 16.1 | review probs 6, SAS program, SAS output |
GLM SAS file, SAS output, R GLM code |
| 35 | 6/18 | Analysis of covariance | Ott, 16.1, 16.2 | SAS ancova1 file, SAS output, R Ancova code |
|
| 36 | 6/19 | Analysis of covariance | Ott, 16.3- 16.5 | forbes data, SAS ancova2 file, SAS output, R Ancova2 code |
|
| 37a, b | 6/19 | Random effects models; mixed effect models |
Ott, 17.1-17.6 | SAS random
effects, SAS output, R random effects |
|
| 38 | 6/20 | Chi-square independence tests | Ott, 10.5 | SAS chi-square test, SAS output, R chi-square code SAS chisq raw data R chisq raw data |
|
| 39 | 6/20 | Review | rev 6 solutions | ||
| 40a, b | 6/21 | Nested designs; Split-plot designs, Repeated measures designs |
Ott, 17.6, 18.2-4 | nested data, SAS nested file, SAS output, R nested code, SAS split-plot, SAS output, R split-plot code SAS rpt measures, SAS output, R rpt measures code |
|
| 6/21 | Exam 6 (due by April 26) | ||||
