Meets: 9:00 - 9:50 MF , 8:15 - 9:05 TT (Problem session 9:00 W ) Room: Madeleva 222
Instructor: Charles Peltier
Office: Mad 214 Phone 4498(H:232-4951) email cpeltier@saintmarys.edu
UPDATE Office Hrs: M 1-2 T 2-3 W 10-11 TH 11-12 F10-11 or see/call me to make an appointmen
Text:
Greenwell, Ritchey, Lial, Calculus for the Life Sciences, Addison Wesley,Boston, 2003.
Peltier, Introductory Statistics Handbook for Math 116, Saint Mary's College, 2003.
Materials:
A calculator with capability for square root, logarithm, and exponential and one-variable & two-variable statistics (mean, standard deviation, correlation & regression) is essential; data storage and built-in formula capabilities of the graphing calculators (TI-8x, Casio fx-7700) are highly desirable. There is an on-line reference for statistical calcualation with popular graphing calculators
We will be using the Minitab statistics program on the campus network. There is an on-line Minitab manual.
Topics:
Calculus
Greenwell, Ritchey, Lial Chaps 7, 8(.1-.3), 11(.1,.3) and some additional notes
Antiderivatives, definite integral and applications, integration techniques, numerical integration and applicationns of integration, differential equations and growth models
Statistics:
(Descriptive): Description of data - grouping, tables, measures of central location and of variation. Correlation and regression. Discrete and continuous random variables - binomial, poisson, normal.
(Inferential): Estimation and hypothesis testing on means, variances, proportions, differences of means (large and small samples)
Use of MINITAB computer package
Applications to the life sciences will be emphasized throughout the course.
Significant non-mathematical contents of the course include explicit awareness of learning and problem-solving skills, the development of independent learning skills, and working in project groups. We will use cooperative group learning, discovery learning, applied critical thinking, problem solving, and regular self assessment.
Attendance: Since you will often be working with your group in class, it is essential that you attend every meeting of the class to fulfill your role in the group. Tests, quizzes, or activities missed because of absence will result in a grade of 0 unless the absence is excused (via Academic Affairs office). In any case, you are responsible for material covered in any class meeting and for handing in work on time.
Assignments: You should expect to be working about 6 - 8 hours per week outside of class time on this course. Regular assignments will be given on a daily basis; you are responsible for remaining current, and for asking questions when they arise. Written assignments will be collected on Thursday, and will be corrected and returned within one week for your studying. You are encouraged to work and study together, but each of you is responsible for her own work and understanding. The list of assignments will be available through the Blackboard site and from the course web page.
I will collect the learning journals (see below) on a rotating basis.Academic honesty policy: You should read the college's statement and policy on academic honesty printed in the student handbook (you are bound by it even if you don't read it) Any violation will result in a grade of 0 for the work involved and a note placed in the files of the Office of Academic Affairs. A second offense will result in failure in the course and notification to the Office of Academic Affairs.
In this course, no references (notes, friends, etc.) may be used on any graded work unless explicit permission is given. For work done out of class, students are encouraged to work and study together, but each student is responsible for her own work and her own understanding. In particular, you must do your own work after any consulatation. For a more detail on the department policy, see Math Department honesty guidelines.
Learning Journal: Each student must keep a learning journal. The purpose is to give you a focus for regular thinking about how you learn effectively - what works, what doesn't, what parts of the course organization help or don't help, what are your strengths as a learner, what areas could use development. Each week you are expected to complete a Weekly Assessment including
1. the most valuable thing learned (about learning or about statistics),
2. the most useful of your strengths (as a learner) used that week and
3. your most important area for improvement in learning, with a
4. plan of action to address the area for improvement.
For each in-class activity, you are to answer the critical thinking questions, which are intended to help you think about the material beyond beyond the specific task of the activity. Leave space for instructor feedback with each week's entry. Feel free to add other related materials, comments and reflections to your learning journal. If you wish, you may use the outline page in the "Course Documents" area of the Blackboard site. I will collect the reflector's learning journal at the first class following the week in which she is the reflector.Team Participation: There is a focus on working in teams in this course. A good portion of your working time will be spent working with your team. You are expected to attend all sessions scheduled by your team.
In-class learning activities: There will be a number of in-class learning activities (about one a week) to be carried out in your learning teams. There are several specific roles [descriptions in the "Course Information" area of the Blackboard site] to be filled in performing this activity, and the team will present a report and written work at the end of the activity. Each activity will also include several critical thinking questions [going beyond the specific task of the activity] to be answered by each team member in her learning journal. At the end of the activity, the team will hand in a report containing (at least)
1. Table of contents
2. Recorders report (including any written work products)
3. Reflector's report * [see below]
4. Team's grade (0.0-5.0) for their teamwork on the activity. (Based on success in completing the learning task and on functioning of the team). I will also assign a grade (0.0-5.0 pts) - if the grade you assign is excessively high, there will be a penalty.
*The reflector's report must include:
1. Role, strength and area for improvement of each participating team member;
2. Greatest strength of the team as a whole [used in this work], two areas most in need of improvement [as shown in this work],
Grades will be based on:
Item Percentage Four in-class tests 45-55 Cumulative final examination 10-20 Homework 5-10 In-class activities (team) 15-25 Data analysis project (individual) 5 Learning journal (individual) 5-10 You will (individually) select percentages in the given ranges so the grading may better reflect your own learning style and preferences. A deadline will be set (about the third week of the semester) for your choice.
The grading scale is based on: 60% < D < 70% < C < 80% < B < 90% < A, with + and - grades occupying the top and bottom 2% of the ranges (No A+ or D- grades).
Test dates: 2/9, 3/2, 4/6, 4/27 Final exam Wed 5/11 8am
Topic outline
| Week | Text sections | Topic |
| 1 | 1.1-7.2 | Review of topics from first semester |
| 2 | 7.2-7.3 | Substitution, the Definite integral |
| 3 | 7.4-7.6 | Fundamental theorem of Calculus, calculation, trig functions, area |
| 4 | 7.6,8.1 | Area Between curves T1(7.1-7.6) Numerical Integration |
| 5 | 8.1-8.3 | Numerical integration, Integration by parts, Applications |
| 6 | 8.3, 11.1(&handout) | Applications, Differential equations and growth models |
| 7 | 11.3, Ch0 | Euler's approximation method T2(8.2-11.2), begin statistics |
| 8 | Ch 0-1 | Basic ideas of statistics, descriptive statistics (1& 2 variable) |
| 9 | Ch 2 | Basic probability |
| 10 | Ch 3 | Discrete random variables - binomial, poisson families |
| 11 | Ch 4 | Continuous random variables, the normal distribution T3 (ch0-4) |
| 12 | Ch 5 , 6 | Distribution of sample means, estimation (t-dist) |
| 13 | Ch 7 | Hyppothesis tests on a population mean |
| 14 | Ch 8 | Inference on a proportion, T4 (ch5-8) |
| 15 | Ch 9, 10 | Inference on difference of means (paired data, independent samples) |
Last updated 1/4/06