BIOMETRY II

503.001

Spring 2001

Instructor:  Jim Belthoff                                                            TIME:  TTh 8:40 – 11:30 am

Office:  SN 217B                                                                        ROOM:  MP 302

Office Phone:  426-4033

email:  jbeltho@boisestate.edu                                                           

Office Hours:  T 2:00 - 4:00 pm, or by appointment

RECOMMENDED TEXTS:

• Design and Analysis of Experiments (1985) by Roger G. Petersen. Marcel Dekker, Inc., New York.

• Computer-Assisted Research Design and Analysis (2001) by Barbara Tabachnick and Linda Fidell.

• Multivariate Data Analysis 5^th Edition (1998) by Joseph Hair et al.

OTHER READING MATERIAL:  Additional articles/reviews/handouts will be provided during the semester.

LEARNING OBJECTIVES: 

1.  Become familiar with common experimental designs and the statistical analysis of designed experiments.

2.  Learn to use SAS® to analyze and interpret data from designed experiments.

3.  Learn to conduct common multivariate procedures and analyses using SAS®.

COURSE ASSESSMENT:

Your outcome in the course will be assessed via the following: 

The in-class exams are designed to assess your ability to recall course material, explain statistical background and theory, and master problem sets.  The project will assess how well you work independently on course material as well as your ability to critically evaluate proposals and communicate important principles and results.

Mid-term Exam 1: 100 points

Mid-term Exam 2: 100 points

Final Exam: 50 points

Project:  100 points

GRADING:

A = 90% or above

B = 80% to 89%

C = 70% to 79%

D = 60% to 69%

F = below 60%

EXAMS:

Exams will include short-answer, essay, problems, or programming questions covering material from lectures, texts, and handouts.  Exams are cumulative in that information covered early in the semester will relate to later information.

HOMEWORK:

Homework (un-graded) will be assigned periodically.  Assignments will usually consist of a research problem along with a dataset to be analyzed.  Students will be expected to describe the design, perform the proper statistical analyses, and prepare small reports (written or oral) on the analyses they conducted and the important conclusions they drew from results.

PROJECT:

Each student will design, propose and conduct an experiment that incorporates topics covered in class.  The proposal will be "peer-reviewed" by classmates, and part of the grade for this exercise will be the quality of the reviews performed.  A final oral report conducted in Powerpoint format will summarize the important results of the experiment. 

ATTENDANCE:

Attendance and participation in class is expected. 

BIOMETRY II - B503

TENTATIVE COURSE SCHEDULE

Spring 2001

TOPIC                                                                                         TEXT CHAPTER

EXPERIMENTAL DESIGN                 

Introduction                                                                                             Ch. 1,2

ANOVA Review                                                                                     Ch. 3

Means Separation Procedures                                                                  Handout

      Estimate Statements

      Contrast Statements

      Least Squares Means

Completely Randomized Design                                                                Ch. 3

Randomized Block Design                     

Latin Square Design                                                                                  Ch. 9

Factorial Experiment                                                                                 Ch. 5

Split Plot Design             

Repeated Measures Designs                                                                     Ch. 6, Handout

Cross-Over Designs                                                                                 Ch. 9

Incomplete Block Designs                                                                         Ch. 10

MULTIVARIATE METHODS                     

Introduction, Multivariate Data, Matrix Algebra                                         Ch. 1,2

Multivariate Analysis of Variance                                                               Ch. 6

Discriminant Analysis                                                                                 Ch. 5

Principal Components Analysis                                                                  Handout

Cluster Analysis                                                                                        Ch. 9

Multiple Regression                                                                                  Ch. 4