(3 credits, 2 hours a week of lecture, 3 hours a week of lab)

SPRING 2008

(TENTATIVE SYLLABUS)

INSTRUCTOR

Office Hours: Tuesday and Thursday 10:30 – 12:00.  If these times are not conducive to your schedule, please set up an appointment.  I will be happy to meet with you as much as needed granted you are putting forth effort to prepare.  Occasionally I will need to travel, attend meetings, etc., and thus I will let you know if I will not be able to attend office hours.

ASSISTANT INSTRUCTOR

TIME AND PLACE

Lecture: Tuesday and Thursday 9:40-10:30 am, Henry H. Chamberlin Forest Resources Complex 207

Lab: Wednesday 1:10-4:00 pm, Henry H. Chamberlin Forest Resources Complex 210

COURSE DESCRIPTION

Collection and analysis of data, probability, frequency distributions, measures of central tendency and dispersion, estimation of parameters, least squares, linear and nonlinear regression, chi-square, analysis of variance. Emphasis on hand- and software-based statistical computations.

COURSE OBJECTIVES

1. To have the ability to communicate with other natural resource managers and the public in general about biological and statistical measurements.

2. Apply rules of probability, and discrete and continuous distributions to determine probabilities in the context of natural resource management.

3. Gain a better understanding of both descriptive and inferential statistics and their application in natural resource management.

4. Obtain an understanding of the utility of correlation analyses in natural resource management.

5. Understand the process behind estimating parameters of regression models and their usefulness in natural resource management.

6. Gain an understanding of the concepts behind comparing population means and sample means and the usefulness of these procedures in natural resource management.

PRE- REQUISITES

MATH 1043 or MATH 1033.  Basically a good understanding of algebra, geometry, and trigonometry at the high school level is required.  Knowledge of statistics is desirable.

TEXTS

Hampton, R.E., and J.E. Havel. 2005. Introductory Biological Statistics, 2nd edition. Waveland Press, Inc., Long Grove, IL. 175 p. (REQUIRED)

Freese, F.  1962.  Elementary Forest Sampling.  Agri. Handbook No. 232.  Southern Forest Experiment Station, USDA For. Serv.  91 p.

http://www.fs.fed.us/fmsc/measure/handbooks/index.shtml

GRADING SYSTEM

There is only one grade assigned for this class.  Grades will be assigned using the following scale.

Lab Assignments = 52% (13 labs worth 100 points each = 1300 points) (75% content, 25% neatness and grammer)

Midterm I = 10% (250 points)

Midterm II = 10% (250 points)

Final Exam = 10% (250 points)

Quizzes = 11% (14 quizzes at 20 points each = 280 points)

Participation = 7% (170 points)

Total number of points is 2500

90% - 100% = A

80% - 89% = B

70% - 79% = C

60% - 69% = D

0 - 60% = F

Lectures

Attendance for lectures will be checked formally. As future professionals, I expect every person to attend lecture because you need to know how to obtain and conduct biological measurements. Attendance records will be used to decide participation and “borderline” grades. For instance, if you regularly attend lecture and your final grade is “89”, I will be highly inclined to give you an “A” for the class. Additionally, if you don’t regularly attend class, yet fail to understand material, that is your choice and you will be held accountable.

Lab attendance is mandatory! This is particularly true given that lab meets only once a week.  All labs will be conducted indoors. 

Unique lab reports are expected from each individual student. Failure to do so will be considered a violation of the University academic honesty guidelines and will result in a complaint filed with the appropriate offices on campus.  Helping other students and asking other students for help is encouraged.  In the professional world, it is good to get second opinions and to ask advice.  As a professional, it is often expected that you help others. With that said, please be wise as to who you ask for help!

The format for lab reports will be discussed during one of the early lab periods. Lab reports must be stapled, and if a lab summary is required, that summary must be typed.  Correct spelling (please use the spell checker of your preferred word processor software), grammar, and numerical reporting are expected on all lab reports and will be graded along with report content. Each person will turn in weekly lab assignments.  Lab assignments are due at the beginning of class the following week (unless I assign another due date). Failure to turn in a lab assignment by the due date will result in points deducted for that lab assignment.  If you must miss a lab session, see me BEFORE you miss lab; or, in the case of an emergency, see me immediately when you return to class. If you have to miss lab for another class, field trip, or school sponsored activity, then you must complete the assignment BEFORE you leave (and I need to have a written letter from the coordinator of the event stating that you will be missing class). If you miss lab without a valid excuse, you will receive a “zero” for that lab assignment.

Percentage of points deducted when a lab assignment or quiz are turned in late:

1 day – 10%

2 days – 20%

3 days – 25%

1 week – 33%

Exams

There will be two mid-term exams and a final exam, each worth 250 points. Exams total to 750 points. You must take the exam at the scheduled time, unless you make prior arrangements with me. Exams will be returned only to review grades, but you will not be able to keep the exams permanently.

If you plan to miss an exam, you have to let me know ahead of time and explain why you will be unable to take the exam at the scheduled time. Unexcused absences from exams result in zeroes.

Academic dishonesty

Policy on academic dishonesty (aka, cheating) is covered in the Academic Code Violations section of the 2007-2009 catalog on pg. 49. Plagiarism will not be tolerated. To ensure that your work is not copied by anybody else, take care how you store your work. Avoid throwing drafts or extra report copies in public/lab trashcans, storing electronic files on public computers, and sharing your finished work with other students, etc. Plagiarism to any degree will result in a “zero” for the assignment, even if somebody stole your work without your knowledge. On the exams, you must work alone. You will receive an automatic “zero” if caught cheating on an exam.

Other examples of cheating include:

The possession, receipt, use, buying or selling, or furnishing of unauthorized help while doing any of the following, but not limited to:

- assignments -reports

- quizzes -term papers

- term papers - tests

- homework (e.g., copying homework assignments from others and/or providing answers)

The use of unauthorized, pre-programmed information (e.g. formulas, facts, definitions) in calculators also constitutes cheating.

When in doubt about the acceptance of providing or getting help for the activities mentioned above, consult your instructor.

Plagiarism:

- Copying directly from a source (e.g. a book or internet site).

- Copying graphics and pictures from the internet without a reference (attribution).

- Paraphrasing without a reference (attribution).

- Submitting someone else’s work.

- Failing to provide a reference (attribution).

When in doubt about plagiarism consult your instructor.

Hats and tobacco products

Whenever you are in a classroom all males should remove their hats.  Additionally, there is to be absolutely no use of tobacco products during regularly scheduled lecture or lab activities.  Intentional failure to meet these rules will be extremely frowned upon by the instructor and may require further action.

Respect

As students preparing themselves to be professionals, it is absolutely necessary to show respect for all individuals within the classroom, this means not only myself, but all other instructors and especially all other students. Additionally, I expect individuals to watch their use of the English language during regularly scheduled lecture or lab activities. If I fail to show respect in anyway, please let me know.

University Policy on Disorderly Conduct (Non-Academic Code Violations section of the 2007-2009 catalog on pg. 36)

Any behavior which disrupts the regular or normal functions of the University community, including behavior that breaches the peace or violates the rights of others.  Disorderly conduct includes, but is not limited to, violent, noisy or drunken behavior, and/or the use of abusive or obscene language on university-controlled property or while representing the University, or attending a university function.  ANY VERBAL ABUSE, PHYSICAL ABUSE OR ENDANGERMENT MAY RESULT IN EXPLUSION FROM THE UNIVERSITY OF ARKANSAS AT MONTICELLO.

University Policy on Verbal Abuse (Non-Academic Code Violations section of the 2007-2009 catalog on pg. 37)

Verbal abuse is the use of obscene, profane or derogatory language which abuses or defames another.  Verbal abuse of any UAM faculty/staff member, or any campus visitor, may result in immediate expulsion from the University of Arkansas at Monticello.

TENTATIVE LECTURE SCHEDULE

WEEK 1.    INTRODUCTION (January 10^th)

WEEK 2.    BASIC STATISTICAL CONCEPTS

                    AND DATA MEASUREMENTS (January 14^th to 18^th) (Hampton and Havel Chapters 1 and 2)

WEEK 3.    DESCRIPTIVE STATISTICS (January 21^st to 25^th) (Hampton and Havel Chapter 4)

WEEK 4.    FREQUENCY DISTRIBUTIONS AND COMBINATORICS AND PERMUTATIONS (January 28^th to February 1^st) (Hampton and Havel Chapters 3 and 5)

WEEK 5.    PROBABILITY AND DISCRETE PROBABILITY DISTRIBUTIONS (February 4^th to 8^th) (Hampton and Havel Chapter 5)

WEEK 6.    THE NORMAL DISTRIBUTION AND INTRODUCTION TO SAMPLING DISTRIBUTIONS (February 11^th to 15^th) (Hampton and Havel Chapters

                6 and 7)

WEEK 7.    STATISTICAL INFERENCE: ESTIMATION AND SAMPLING DISTRIBUTIONS (February 18^th to 22^nd) (Hampton and Havel Chapter 7)

WEEK 8.    STATISTICAL INFERENCE: HYPOTHESIS TESTING AND THE ONE-SAMPLE T-TEST (February 25^th to February 29^th)(Hampton and Havel        

                    Chapter  8)

WEEK 9.    INFERENCES CONCERNING TWO POPULATIONS AND PAIRED COMPARISONS (March 3^rd to 7^th) (Hampton and Havel Chapter 9)

WEEK 10.  INFERENCES CONCERNING MULTIPLE POPULATIONS: ANOVA (March 10^th to 14^th) (Hampton and Havel Chapter 10)

WEEK 11.  SPRING BREAK (March 17^th to 21^st)

WEEK 12   ADDITIONAL ANOVA DESIGNS (March 24^th to 28^th) (Hampton and Havel Chapter 11)

WEEK 13.  CORRELATION (March 31^st to April 4^th) (Hampton and Havel Chapter 13)

WEEK 14.  NO LECTURES (April 7^th to 11^th)

WEEK 15.  REGRESSION ANALYSIS (April 14^th to 18^th) (Hampton and Havel Chapter 12)

                      QUIZ13_EstimatingParameters

WEEK 16.  ANALYSIS OF FREQUENCIES (April 21^st to 25^th) (Hampton and Havel Chapter 14)

WEEK 17. OPEN (April 28^th to 29^th) (Hampton and Havel Chapter xx)

TENTATIVE LABORATORY SCHEDULE

WEEK 1.  SAMPLING ERROR AND SAMPLING DISTRIBUTIONS

(January 9^th)

Sample distribution versus sampling distribution

WEEK 2.  STATISTICAL CONCEPTS AND DATA MEASUREMENTS  (January 16^th)

WEEK 3.  DESCRIPTIVE STATISTICS (January 23^rd)

                    Excel spreadsheet for Lab 3 exercises

WEEK 4.  FREQUENCY DISTRIBUTIONS AND COMBINATORICS AND PERMUTATIONS (January 30^th)

WEEK 5.  TEST 1 (February 6^th), FROM WEEK 1 TO WEEK 4 MATERIAL

WEEK 6.  PROBABILITY AND THE NORMAL DISTRIBUTION (February 13^th)

WEEK 7.  STATISTICAL INFERENCE: ESTIMATION AND SAMPLING DISTRIBUTIONS (February 20^th)

WEEK 8.  STATISTICAL INFERENCE: HYPOTHESIS TESTING AND THE ONE-SAMPLE T-TEST (February 27^th)

WEEK 9.  INFERENCES CONCERNING TWO POPULATIONS AND PAIRED COMPARISONS (March 5^th)

WEEK 10.  TEST 2 (March 12^th) FROM WEEK 5 TO WEEK 9

WEEK 11.  SPRING BREAK (March 17^th to 21^st)

WEEK 12.  ANOVA (March 26^th)

WEEK 13.  CORRELATION (April 2^nd)

                    Excel spreadsheet for Lab exercises

WEEK 14.  SAMPLING ERROR AND SAMPLING DISTRIBUTIONS (April 9^th)

WEEK 15.  REGRESSION ANALYSIS (April 16^th)

WEEK 16.  OPEN (April 23^rd)

CORE COMPETENCIES

BASIC ADVICE ABOUT BIOMETRICS

Most of you probably come from a natural resource background, and in many ways are probably more prepared than I was when I first started my education in Forestry. Although you may not have basic knowledge about all topics discussed in this class, please use common sense for all assignments. For example, please don’t tell me that a loblolly pine tree is 390 feet tall, that deer weigh 3000 pounds, etc. There are many resources available to you that should help you determine what answers are reasonable for any question. These resources include myself, teacher assistants, other professors here at UAM, perhaps members of your family, your fellow undergraduate students as well as graduate students, and books and journals.

STUDENTS WITH DISABILITIES

ACKNOWLEDGEMENTS

I would like to thank the following people for providing guidance about the content and organization of this class. 

Dr. Paul F. Doruska, University of Wisconsin-Stevens Point, Stevens Point, WI

Dr. David R. Larsen, University of Missouri-Columbia, Columbia, MO