Class Restriction And Registration Summary

 

BIOS 40411 - Section 01: Biostatistics (CRN 22067)


Course Description:
Basic principles of statistical analysis and their application to biological problems, including statistical inference, analysis of variance, regression, non-parametric approaches, and introduction to statistical computing. This course's "lab" is a tutorial; it does not fulfill the laboratory elective requirement (after 1993). Students may not take both BIOS 40411 and MATH 20340. Spring.

Associated Term: Spring Semester 2012
Campus: Main
Credits: 4
Grade Mode: Standard Letter
Course may not be repeated


Prerequisites:
(BIOS 10162 or BIOS 20202) and (MATH 10360 or MATH 10560 or MATH 10860 or MATH 10460)

Corequisites:
BIOS 42411

Comments: Co-requisite: BIOS 42411 Section 01, 03, 05, 07, or 09; taught concurrently with section 02

Restrictions:
Must be enrolled in one of the following Major(s):
Biological Sciences (BIOS) ,  Environmental Sciences (ES) ,  Environmental Sciences (Supp.) (ES2)
Must be enrolled in one of the following Levels:
Employee Non-Degree (EM) ,  St. Mary's College (SM) ,  Undergraduate Non-Degree (UD) ,  Undergraduate (UG)
Must be enrolled in one of the following Campuses:
Main (M)

Cannot Have Taken:
MATH 20340

Course Attributes:
CHSE - CHEM Science Electives ,  EETE - EE Technical Electives ,  ZTST - Final exam

Registration Availability (Overflow: Off )
  Maximum Actual Remaining
TOTAL 85 79 6



Crosslist Information
Class Information Maximum Actual Remaining
BIOS  40411 01, CRN 22067  (Primary) 85 79 6
BIOS  40411 02, CRN 28295   40 36 4
Total 125 115 10
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Instructor's Description of Course » Lamberti, Gary » BIOS  40411 - Section 01:  Biostatistics (CRN 22067)
This section presents the instructor's preliminary design of the course. It is intended to help students gain a general sense of what the course will be like.
Course Objectives
To prepare students in the design of biological experiments and the statistical analysis of biological data
To familiarize students with the fundamental statistical tests available for data analysis
To gain a facility with the types of computerized statistical packages commonly used to analyze biological data
Use of Class Time Extent (0-3 scale)
Lab work
Lecture: present material not in the readings
Lecture: review/elaboration of reading material
Quizzes or tests
Class discussions or case study reviews
Cooperative learning (small groups)
Data generation during in-class experiments
In-class exercises, simulations/games, or problem set work
Instructor demonstrations
Student presentations
Kinds of Assignments or Learning Activities Emphasis (0-3 scale)
Problem-solving or computational exam questioning
1-2 page essays, arguments, reflection papers, or question sets
Class attendance
Computer programming
Free-response, essay, or short-answer exam questioning
Lab research and reports
Problem sets/exercises
3+ page essays, reflection papers, arguments, or analyses
Design projects
Group student presentations
In-class participation
Individual, original research projects or interviews
Multiple-choice, matching, or true-false type exam questioning
Quizzes
Reading
Term/research papers (less than 10 pages)
Types of Reading Materials Extent (0-3 scale)
Exercise or problem sets collection
Other instructor-written handouts
Lecture notes or supplements
Textbook
Journal/research articles
Popular press (newspapers, magazines, etc.)
Reference materials
Role of teaching assistants (TAs)
Grade examsessays, problem solutions, or other open-ended items
Grade examsT/F, multiple choice type items
Hold office hours
Read/grade assignments/homework
Deliver one or more lectures
Facilitate/supervise lab sessions or studio work
Lead group help sessions
Facilitate discussion sections
Enrollment History » BIOS 40411 Biostatistics (CRN 22067)
Enrollment over the last three years
Course was recently taught in SP09, SP10, SP11
Average number of students: 86
Composition of Students First Year Soph Junior Senior/5th Grad/Prof
FYS          
Architecture          
Arts and Letters     1% 3%  
Business          
Engineering         1%
Science   6% 23% 62% 4%
Law          

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