ENS 205
Environmental Data Analysis Science Center 106
Fall 2002

Dr. Rosanna Cappellato

Science Center 106, email: rcappell, phone: x-2604

 

Course Syllabus and Schedule


Objectives: The purpose of this course is to introduce you to the practice of manipulating, analyzing, and presenting quantitative information for the environmental studies and sciences. While the examples and problems you will work with in this class will primarily pertain to the environment, the procedures you will learn are generic, the techniques you learn are basic, and the tools are standard. That is, what you learn in this course can and should be applied to data analysis in virtually any field. The emphasis in this class will be on the understanding and application of basic data analysis techniques. You will be expected to use what you learn here in subsequent ENS courses and in your senior project, if appropriate.

Textbook: Data Analysis with Microsoft Excel, by K. Berk and P. Carey. Duxbury/Thomson Learning, Pacific Grove, CA: 2000. Available at the AU Bookstore or amazon.com.

Grading: All grades will be divided along traditional numerical lines (>= 90% of points = A range; 80-89% of points = B range; 70-79% of points = C range, etc.).

LATE ASSIGNMENTS WILL NOT BE ACCEPTED UNLESS PRIOR PERMISSION IS OBTAINED FROM THE INSTRUCTOR. IF A SCHEDULE CONFLICT EXISTS FOR A TEST, THE STUDENT MUST TAKE THE TEST EARLY. MAKE-UP TESTS WILL NOT BE GIVEN.

Hour Exams 30%
Homework, In-Class Assignments 20%
Independent Project 30%
Final Exam 20%


Attendance: Regular attendance is expected, but will not be checked. You are responsible for all material presented during class time, regardless of whether you were there or not.

Communications: I will use the AU email system frequently and regularly. If you do not receive email via the regular AU system, it is your responsibility to inform me of an alternative email address to use for you. I don’t care what address I send things to, but I expect you to read your mail on a regular basis (i.e. at least every day).

Tentative Schedule

Week Topics Text Chapter
Sept 2 Intro to class, kinds of data, interpreting graphs, survey  
Sept 9 Intro to spreadsheets & Excel, survey data input 1 and 2
Sept 16 Data visualization, charts and graphs 3
Sept 23 Variability & error in data, sampling, descriptive statistics 4
Sept 30 Distributions and Probability 5
Oct 7 Distributions and Probability, continued; 1st Hour Exam  
Oct 14 Experimental Design and Hypothesis Testing 6
Oct 21 Testing for Differences: t-tests, p-values, confidence intervals 6
Oct 28 Testing for Differences, continued  
Nov 4 Testing for Associations, Tables, Chi Square 7
Nov 11 Testing for Relationships, Regression & Correlation 8
Nov 18 Testing for Relationships, continued; 2nd Hour Exam 9
Nov 25 Project Work  
Dec 2 Project Work  
Dec 9 Project Work  

Thursday, December 19th Final Exam 1:15-3:15 pm