Andrew D. Taylor, Department of Zoology, University of Hawaiʻi at Mānoa

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Biometry (Zool 631)

final exam ID numbers
(the exam and data are on Laulima, not this site)

Lecture schedule

Current assignments:

 

Assignment

Data

Solutions

Homework

HW # 14, due Friday 9 Dec.

solutions

HW # 13, due 2 Dec.

IBI data
  Excel

solutions

Discussion

Disc. # 12, 7 / 8 Dec.

Halimeda
  Excel

solution

Disc. # 11, 30 Nov. / 1 Dec.

guinea grass
  Excel
  text

solution

Readings

Handouts

Minitab resampling macros


email contacts:

  • the class: zool631-l@lists.hawaii.edu

  • me: taylor@hawaii.edu

  • Dave Lin (TA) : davidlin@hawaii.edu

Overview of the course

Syllabus

This is an introductory (though fast paced) course on data analysis, with some coverage of how to design studies to obtain useful data. The methods covered (like the textbook) are not specific to biology. The examples used in lecture, as well as the assignments for many of the discussions, do however use biological data, in almost all cases from studies conducted by the instructor or other U.H. researchers.

This course covers only the most basic methods, dealing with at most two variables (one response variable and one explanatory variable). The sequel, Advanced Biometry (Zool 632) covers most methods for analysis of one quantitative response variable and any number and combination of explanatory variables. There are a few courses on more advanced methods (e.g. categorical data analysis, multivariate analysis) scattered in other departments at U.H., and from time to time I teach topic courses on advanced methods specific to biology (e.g. multivariate analysis in community ecology).

There are three lectures per week, one discussion, and (typically) one homework set. Homework assignments are exercises from the textbook. Discussion assignments are more open-ended, usually involving analysis of real data; for most students these are the most valuable parts of the course.

No prior knowledge of statistics is assumed, though the course will be difficult to appreciate without some experience conducting research, or at least reading the primary scientific literature. Similarly, no prior knowledge of statistical software is required; students can use any other software if they wish (and already know how) but for beginners Minitab is recommended.

Text:

David S. Moore, George P. McCabe & Bruce A. Craig. Introduction to the Practice of Statistics. W.H. Freeman & Co. [The current edition is the 7th;earlier editions can be used also.]

http://bcs.whfreeman.com/ips7e/