Experimental Methods in Exercise and Nutritional Sciences

ENS 601

Dr. Susan Levy

 

Office:           ENS 302

Phone/email:  594-5672; slevy@mail.sdsu.edu

Office Hrs:     Monday: 2:00 – 3:30 PM; Wednesday: 2:00 - 3:30 PM; or by appointment

 

Course Description: This course will focus on the use of statistical procedures most common to the Exercise and Nutritional Sciences. The course begins with a brief overview of basic statistical concepts and moves on to cover the various statistical techniques used in our area of study.

 

Course Objectives:

Upon completion of this course the student should be able to:

·       Demonstrate an understanding of statistical software to create and analyze data.

·       Demonstrate an understanding of inferential statistics.

·       Use and interpret independent t-tests.

·       Use and interpret one-way analysis of variance (ANOVA).

·       Use and interpret repeated measures designs.

·       Use and interpret two-factor factorial designs.

·       Use and interpret correlation and regression.

·       Select the appropriate statistical technique for use in answering a research question.

·       Demonstrate an understanding of when multivariate techniques are appropriate.

 

Course Materials:

Text:   Glass, G.V., & Hopkins, K.D. (1996). Statistical methods in education and psychology (3rd ed.). New York: Allyn & Bacon.

 

Class Notes Packet:    KB Books.

 

Evaluation Criteria:

Exam 1           25%

Final Exam     25% (Tuesday, December 16, 2003; 3:30 – 5:30 PM)

Assignments    20%

Project           30%.

 

Course Grading:

 

 

90-100%

A

80-85%

B

70-75%

C

60-65%

D

88-89%

A-

78-79%

B-

68-69%

C-

58-59%

D-

86-87%

B+

76-77%

C+

66-67%

D+

Below 58%

F

 

 

Course Outline:

                                                                                                 Text Readings

I.         Background Overview                                                      Chapters 1, 2

A.    Inferential Statistics                                                     pp. 49 – 102

B.    Concepts and terminology                                           pp. 255 – 282

C.    Use of statistical software

 

II.       Design and Analysis of the Simple Experiment                   

A.    The t-test                                                                   Chapter 12

B.    One-way analysis of variance (ANOVA)                       Chapter 15, 17

C.    Statistic Power                                                           pp. 262 - 269

D.   One-way repeated measures ANOVA                           Chapter 20

E.    Analysis of covariance (ANCOVA)                              Chapter 21

III.      Design and Analysis of the More Complex Experiment       

A.    Two-factor factorial design                                          Chapter 18

B.    Two-factor mixed design

IV.      Correlation                                                                     

A.    Bivariate correlation                                                    Chapter 7

B.    Simple regression                                                        Chapter 8

V.       Introduction to Multivariate Methods                                  

A.    Multiple Regression

 

            

Computer Lab Hours [Love Library] 594-3189

 

Monday – Thursday     7:00 am   – 11:45 pm

Friday                         7:00 am   –   5:45 pm

Saturday                    10:00 am   –   5:45 pm

Sunday                      10:00 am   – 11:45 pm

 

 

 

Please note:

If you have a documented disability and anticipate needing accommodations in this course, please make arrangements to meet with me soon. Please request that the Disabled Students Services provide a list of needed accommodations.

 

 

 Additional resources that you may find useful

 

Rowntree, D. (1981). Statistics without tears. New York: Charles Scribner’s Sons.

 

Vincent, W.J. (1999). Statistics in kinesiology. Champaign, IL: Human Kinetics.

 

Tabachnick, B.G., & Fidell, L.S. (2001). Computer-assisted research design and analysis. Boston: Allyn and Bacon.