Instructor: Steven Juliano

Office:  335 FSA

Phone:  438-2642  

e-mail:  sajulian@ilstu.edu

Web: http://www.bio.ilstu.edu/juliano/juliano.htm 

Lecture: 

MWF 11:00 – 11:50 AM FSA 125

Laboratory:  

T 1:00 - 3:50 PM SLB 121

Office Hours: 

M & Th 2:30 PM (tentative)

 

TEXTS:        Biometry 3rd ed., R. R. Sokal & F. J. Rohlf.  W. H. Freeman, 1995

                      Statistical Tables 3rd ed., F. J. Rohlf & R. R. Sokal.  W. H. Freeman, 1995

                     A Step-by-Step Approach to using SAS for Univariate and Multivariate Statistics, 2nd ed.,  

N. O’Rourke, L. Hatcher, E.J. Stepanski  SAS Institute Inc., 2005

                      Biostatistics Manual, S. A. Juliano, Phi Sigma, 2006

 

COURSE GOALS:  This course is an introduction to applied statistics.  The  ideas and methods discussed will be those most relevant to biologists in general.  You will acquire a working knowledge of basic statistical methods, and will be able to determine which procedures are most appropriate for a given circumstance.  All of the statistical techniques relevant to biologists cannot be covered in one semester, however, once you have mastered the material in this course, you will be better equipped to understand and use more advanced statistical methods.

 

In the laboratory portion of this course you will gain experience in the use of the SAS computer package for statistics.  There are a number of good statistical packages available, and some of you may already know how to use some of these. I will give examples and explain how to do things in SAS, and all of you will do the assignments using SAS. By  learning enough about general aspects of statistical computation and interpretation,  you will be able to generalize to other packages if you so choose.

 

GRADE:  Although BSC 490 and 420.27 are nominally two different courses, in reality they are part of a single course.  You  will receive the same grade in both courses.  Course grades will be determined as follows

 

Course Component

Percent of Final Grade

 

Total Score

Yields Final Grade

Exam I

17.5%

 

>85%

A

Exam II

17.5%

 

75 - 85%

B

Cumulative Final Exam          (in class)

20.0%

 

65 - 75%

C

                                           (take home)

10.0%

 

55 - 65%

D

10 Homework Assignments

35.0%

 

<55%

F

 

Homework will involve computer problems.  Specific instructions on how to write up the report and what to include will be provided.  In addition to homework assignments, I will give sets of study problems that will not be graded, but which will help you to learn the material.  Some exams will be open book - open note and will contain problem solving questions, therefore, you should have a calculator.  Some exams will include take-home sections, which will be similar to the homework assignments.  Homework and take-home exams will not be accepted late.   Turning in an incomplete homework assignment will produce a  much better grade and learning experience than will turning in nothing at all.  The 10 homework assignments, and tentative due dates are:

 

Assignment

Topics

Tentative Due Date

1

Summary Statistics

Tuesday 29 Aug.

2

Simulating data & Generating Random Numbers

Tuesday 5 Sept.

3

One sample tests

Tuesday 12 Sept.

4

Two sample tests

Tuesday 26 Sept.

5

One-way Fixed effects Analysis of Variance

Tuesday 3 Oct.

6

One-way Random  effects Analysis of Variance

Tuesday 10 Oct.

7

Two-way Factorial Analysis of Variance

Tuesday 24 Oct.

8

Two-stage nested Analysis of Variance

Tuesday 14 Nov.

9

Linear & Multiple Regression

Tuesday 28 Nov.

10

Analysis of Covariance

Tuesday  5 Dec.

COURSE OUTLINE

 

                                                                Reading Assignment

                                                                (Sokal & Rohlf 1995

Topic                                                     Biometry)

---------------------------------------            ------------------------------

Introduction                                          pp. 1-5

   Kinds of variables                             pp. 10-19

   Frequency distributions                  pp. 19-31

   Random samples & populations    pp. 8-10

 

Descriptive Statistics                                                                              

   Location and dispersion                  pp. 39-59

   Relationships                                     pp. 555-574

   Statistics vs. parameters                 pp. 52-53

 

Probability                                                                                        

   Concepts                                            pp. 61-71

   Distributions                                      pp. 71-95

   Normal distribution                           pp. 98-125

 

Estimation                                                                                            

   Point vs. interval estimates             pp. 127-152

   t-distribution                                      pp. 143-152

   c2 distribution                                    pp. 152-157

 

Hypothesis testing                                  

   Null and alternative hypotheses   pp. 157-175

   Assumptions                                     pp. 392-409

   Type 1 and type 2 errors                  pp. 158-159

   t-tests                                                  pp. 169-175; 223-227;

                                                                                404-406

   One tailed vs. two tailed tests          pp. 79-80; 168-169

 

Failure to meet assumptions

   Examples and consequences                         

   Transformations                                pp. 409-422

   Nonparametric tests                         pp. 427-431

 

EXAM I - tentatively scheduled for 19 September, during the lab period

 

Analysis of variance  

   Assumptions and the model           pp. 179-205

   One way ANOVA                       pp. 207-223

   Orthogonal contrasts                       pp. 229-240; 521-531

   Multiple comparisons                      pp. 240-265

   Fixed vs. random effects                  pp. 201-205

   Two way ANOVA                            pp. 321-363

   Factorial designs                               pp. 369-389

   Unbalanced designs                         pp. 357-363

   Nested designs                                 pp. 272-317

   Failure of assumptions                     pp. 392-422

 

 

                                                                Reading Assignment

                                                                (Sokal & Rohlf 1995

Topic                                                     Biometry)

---------------------------------------            ------------------------------

Nonparametric analogs of ANOVA                                                 

   Assumptions

   Kruskal-Wallis test                           pp. 423-431

   Friedman's test                                  pp. 440-447

   Follow up tests                                  pp. 431-434

                               

Experimental design                                                                            

   Randomization                                                                                             

   Replication

   Control

   Experimental units

 

EXAM II - tentatively scheduled for 31 October during the lab period

 

Regression                                                                                           

   Assumptions                                     pp. 451-455

   Reasons for doing regression         pp. 486-491

   Linear regression                              pp. 455-486; 491-493

   Failure to meet assumptions           pp. 531-541

   Geometric mean regression             pp. 541-549           

   Comparing regression lines             pp. 493-499      

   Analysis of covariance                    pp. 499-521

   Polynomial regression                      pp. 665-681

   Multiple & stepwise regression    pp. 609-664

 

Correlation                                            pp. 371-395

   Assumptions                                                                                    

   Relationship to regression                                                             

   Partial correlation                   

   Nonparametric correlation             

 

Frequency data                                                                   

   Proportions                                                                                       

   Goodness of  fit                                 pp. 685-722          

   c2  vs. likelihood ratio                       pp. 689-692

   Contingency tables                          pp. 724-740

   Fisher's exact test                              pp. 730-736

 

Miscellaneous Methods                                                    

   Combining probabilities                   pp. 794-797                                           

 

CUMULATIVE FINAL –

                Tuesday, 13 December, 8:00 AM -11:00 AM - Take home part due by 5:00 PM Friday 15 December

 

Laboratory Schedule

 

Date   

Laboratory Topics

(readings in A Step-by-Step Approach to using SAS for Univariate & Multivariate Statistics TBA in lecture or lab)

22 August                  

Introduction to SAS; Data entry; Data manipulation; Summary Statistics

 

29 August      

Generating & working with random numbers

 

5 September  

One sample t-tests; Wilcoxon tests

 

12 September 

Two sample t-tests; Wilcoxon two sample tests

 

19 September 

Exam I

 

26 September 

One way ANOVA (fixed); Testing assumptions; Contrasts; Multiple comparisons; Nonparametric

 

3 October                  

One way ANOVA (Random); Estimating variance components

 

10 October                

Two Way ANOVA; Interactions;

 

17 October                

More Two Way ANOVA; Unbalanced designs; Least Squares Means for multiple comparisons

 

24 October                

Mixed Model ANOVA

 

31 October

Exam II

 

 7 November

Two Stage Nested ANOVA; Estimating variance components

 

14 November

Linear & Multiple regression; Residuals; Testing assumptions

 

21 November

Thanksgiving break

 

28 November

Analysis of covariance; Testing homogeneity of slopes; Estimating separate slopes

 

 5 December

Loose ends/Review

 

 

Notes on the SAS manual

 

It is essential that you read the assignments before coming to lab.  This is particularly true for the first two weeks, when you will be learning about how to use SAS.  Learning how to use SAS is vital to your success in this course, your sanity, and probably your success as a research student.

 

This SAS manual is also a reference.  Have it with you when you use the computer.  I believe you will find it helpful, both now and in the future.  You will probably not find this manual an entertaining and stimulating read -- it is a computer manual, after all.