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QSci 381B: Introduction to Probability and Statistics
Gordon Holtgrieve, Assistant Professor, School of Aquatic and Fishery Sciences
Office: Fishery Sciences Building (FSH) 316B; Office phone: Don't bother...I never answer it; Email: email@example.com
Office hours: I will be available for drop-in consultation Wednesdays from 1:00-3:00 pm. Otherwise I am available for individual appointments (which should be initiated after class or by email).
Jennifer Lang: Office hours: Mondays from 1:00-3:00 pm in Fishery Sciences Building (FSH) 221; Email: firstname.lastname@example.org.
Daniel Feinberg: Office hours: Tuesdays from 1:00-3:00 pm in Anderson (AND) 14; Email: email@example.com.
Course Schedule and Location
The official text for the B section of QSci 381 is Elementary Statistics: Picturing the World (6th Edition) by Larson and Farber. Note: The A section uses a different text so be sure you have the right one! If you want to use an older edition of the text also note that the graded homework questions will all be from the 6th edition text. Thus you will need to get the questions from either a classmate or the copy placed on reserve in the Odegaard Undergraduate Library.
This class is designed to teach undergraduate natural science students basic probability and inferential statistics. There are three main sections to the course: data summarization, probability theory, and testing hypotheses. Specific learning goals include:
- Understand the difference between descriptive and inferential statistical methods.
- Learn how to formulate a hypothesis, design an experiment or sample survey, collect and analyze sample data, interpret the results of the analysis, make the proper conclusion, and draw the correct inference.
- Understand the power of inductive logic and its role in gaining a better insight into biological and environmental problems.
- Demonstrate the proper uses of statistical thinking and the role statistics plays in science and in the common press.
- Allow students to better understand how statistics can be properly used in their disciplinary studies in biology, natural resource sciences, environmental sciences, and other physical and social sciences.
Format & Structure
The class will emphasize fundamental principles of data and statistics, presented in lecture and lab format, and reinforced by:
- Graded weekly homework assignments
- Graded computer lab exercises
- Two in-class, closed book midterm exams
- A comprehensive final exam
The grades for this class will be determined as follows:
|Assignment||Points||Percent of grade|
|Homeworks (9 in total)||50 (450 total)||25|
|Computer labs (9)||50 (450)||25|
|Midterms (2)||270 (540)||30|
|Final (1)||360 (360)||20|
Note that homework and lab exercised comprise 50% of your grade. I do reserve the right to adjust the grading scheme to account for unforeseen events or issues. In the event the grading scheme is changed, it will both be revised here and announced via class email.
Do not let yourself get behind in this course. There are a number of mechanisms for you to get extra help if need. Your first stop should be your section TA. The Statistics Department also offers a Tutor and Study center, information for which can be found here: www.stat.washington.edu/tutorcenter/. There is also the CLUE Study Center in Mary Gates Hall with drop-in stats tutoring Sundays & Thursdays from 7p-12M. Finally, I encourage you to work along side your fellow students, but always be mindful the goal is to collaborate, not copy.
Plagiarism, cheating, and other misconduct are very serious violations of your contract as a student. I expect that you will know and follow the University's policies on cheating and plagiarism. Any suspected cases of academic misconduct will be handled according to University regulations. More information can be found at: http://depts.washington.edu/grading/issue1/honesty.htm (Links to an external site.). Be advised that instructors at the UW (including TAs) have the responsibility to notify University Conduct Committees about any suspected student misconduct. You should expect we will report all cases of misconduct without fail. Also, be advised that even though this is a "numbers" course, copying the work of others is really easy for us to identify and prove. Don't risk it....please.
Late Assignments and Re-grade Policy
As a matter of policy, late assignments will not be accepted unless you have notified the instructor well in advance or the circumstances are beyond your control. I (Holtgrieve) have full discretion over whether to accept a late assignment. If you feel an assignment has been graded inappropriately, submit a request for a regrade to your TA over email and cc the instructor. In your email, include a brief description of why you feel the grade does not accurately reflect the quality of the work along with the graded assignment. Grade appeals must be submitted within one week of receiving the graded assignment. Note that we will regrade the entire assignment.
Email and Computer Use
All students are expected to have a working email address and you will receive email relevant to this course on a regular basis. We will use Canvas manage the course schedule, make announcements, manage grades and in some cases deliver/collect assignments. Students are also expected to regularly check the UW Canvas site for updates relevant to the course.
To request academic accommodations due to a disability, please contact Disabled Student Services, 448 Schmitz, (206)543-8924 (V/TTY). If you have a letter from Disabled Student Services indicating that you have a disability that requires academic accommodations, please present the letter to the instructor within the first two weeks of the course so we can discuss the accommodations needed for this class.
The syllabus page shows a table-oriented view of the course schedule, and the basics of course grading. You can add any other comments, notes, or thoughts you have about the course structure, course policies or anything else.
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