MAT 210, Introductory Statistics -- Spring 2015
course URL: http://faculty.taylor.edu/knconstantine/mat210/mat210.htm
The above webpage is your source for class outlines, homework assignments, occasional news items & homework hints, and an up-to-date schedule of topics. You can access the webpage directly or using a link I’ve built under Blackboard’s “course documents”.
philosophy:
We're a team! You can count on me for diligent work on our course and a welcome to my office for questions about the course (or life in general). I'll count on you for diligent work on our course, help to classmates, and contributions in class!
student goals:
- to develop your ability to “produce” basic statistical work, i.e.
a) gathering data sensibly
b) describing data helpfully
c) drawing conclusions appropriately
d) communicating implications clearly
- to develop your ability to “consume” statistical reports critically, i.e.
a) critiquing limitations of methods
- to practice the use of statistical methodology in a substantive project
- to enhance your ability to solve problems and communicate clearly
prerequisite: none listed in the catalog
instructor: Professor K. Constantine
office: ESC 125
hours: MTWRF, 1:30-2:30 pm (or by appointment)
email: office)
home) [checked each morning by 5am]
homepage: http://www.css.tayloru.edu/~knconsta/www
class sessions:
§ MTWF, 9am-9:50am, Euler 118
text:
§ Utts & Heckard’s Mind on Statistics (fourth edition)
additional references:
· Jessica Utts’ Seeing Through Statistics [easier level; ask me]
· the video series Against All Odds
other tools:
§ We will need for at least half the class to bring laptop computers to class on many class days.
§ I will assume that everyone will have a graphing-type calculator for use in class, on homework, and on exams/quizzes. The class Blackboard site has some TI-89 and TI-86 programs that you can download.
§ I will expect you to make use of the computer package Minitab which is available on the campus network –OR- can be downloaded for trial/rental/purchase from:
http://www.onthehub.com/minitab/minitab_english.htm [underscore before “english”]
GRADING:
hour exams (3) / 600 / 250 for your best percentage, 150 for lowest, 200 for remainingproject / 200 / info below
final exam / 200
quizzes/HW/groups/etc. / 200 / info below
TOTAL / 1,200
Your final letter grade will be based on a "raw score" as above with these grade cutoffs:
§ A-range 87.5%
§ B-range 75.0%
§ C-range 62.5%
§ D-range 50.0%
· hour exams:
o No provision for makeup exams is planned. In the event that you have a BONAFIDE reason to miss an exam, you MUST notify me in advance.
o grading:
§ My evaluation of your responses to exam questions will be based on correctly demonstrated use of course concepts/methods.
§ Arithmetic errors (which do not result in implausible answers) will earn little (if any) point deduction.
§ Correct answers which are not explained using course concepts/methods will earn few (if any) points.
§ I will grade what you write. If your response is unorthodox but correct, it will get full credit.
· project: [done in teams]
o Presentations will be made to the class on a date TBD in May.
o Written reports will be due to me by 4pm on May 13. No late reports will be accepted. Report expectations are given below.
o A printout of your full data is due on a date TBA.
o You must secure my approval for your project by TBA.
· final exam: Wednesday, 20 May, 1-3pm.
Please do not schedule conflicts (academic or travel or any other); I cannot grant exceptions. They have to be approved in Freimuth Hall.
· quizzes:
o Quizzes may be given periodically, either electronically or in class. Their primary purpose is to ensure that you’re reading the text thoughtfully.
o I may drop your lowest quiz score.
· homework:
o Assignments will be given for each class session. I will expect you to have them completed for submission by the date posted on the Homework link of our course website.
o Write up your solution to each problem in such a way that you can give it to a classmate and he/she can follow your steps and rationale.
o Solutions to all homework problems will be posted online after the due date. The postings will be as links on the homework webpage.
Team Work:
In the first week of class you will be assigned to a team of 3 or 4 class members. You are encouraged to work with your teammates on general course assignments but you will be mandated to work with them on your course project.
attendance:
· Our guiding philosophy will be twofold: Your full and prompt attendance is imperative to (1) your own understanding/appreciation AND (2) that of your classmates.
· Our policy will be that each unexcused absence after 4 will cause your grade to drop by one “notch”, e.g. B+ to B. Unexcused late arrivals will count as half an absence and the number of absences will be rounded up for purposes of this policy.
excerpt from a paper I wrote for a TU faculty course on Integration of Faith & Learning:
What is Statistics?
Statistics is, arguably, a separate discipline at the interface of science (in the broad sense), mathematics, and epistemology.
Statistics presupposes that there is a reality to be discovered but that it is disclosed to us only via limited, imperfect, variation-laden data. In the face of such randomness, we seek to make inferences which correspond to true reality. Thus we don’t know if what we’re saying is true or false, but our goal is correspondence with reality and an explicit understanding of the extent of our uncertainty. Perhaps Statistics’ closest disciplinary kin is Journalism.
Statistics culture has a deeply ingrained sense of ethics, primarily in letting data speak for themselves. Any statistician who appears to be using methods as a persuasive weapon would be frowned upon. The motivation for this sense of ethics is usually articulated as both professional integrity and concern for the implications of conclusions we help researchers to draw. For some Statisticians, the basis for these ethical concerns may be religious; for others it may not be religious. In any case, the ethical concern is pervasive and deep in the Statistics community.
The following information is expected in all TU syllabi. I will take for granted that you understand the ethical reasons behind the policies and the implications of the policies.
Plagiarism:
Definition: In an instructional setting, plagiarism occurs when a person presents or turns in work that includes someone else’s ideas, language, or other (not common-knowledge[1]) material without giving appropriate credit to the source. Plagiarism will not be tolerated and may result in failing this course, and may also result in further consequences as stipulated in the Taylor catalogue: http://www.taylor.edu/academics/registrar/policy_academic_integrity.shtml
Academic dishonesty constitutes a serious violation of academic integrity and scholarship standards at Taylor that can result in substantial penalties, at the sole discretion of the University, including but not limited to, denial of credit in a course as well as dismissal from the University. . . . In short, a student violates academic integrity when he or she claims credit for any work not his or her own (words, ideas, answers, data, program codes, music, etc.) or when a student misrepresents any academic performance. Please see the catalogue for a complete statement: http://www.taylor.edu/academics/registrar/policy_academic_integrity.shtml
Project Information
Rationale:
§ to have you practice the steps described on page 7 (of textbook) in a substantive project which is of interest to you
§ to have you work with a team on this project
Requirements & deadlines:
- [plan to me by TBD #1D] Formulate questions (about some population) which are of interest to you.
- [also in plan to me by TBD #1] Develop a plan for gathering data.
a. How will you select persons or items to provide data?
b. How many persons or items will you select?
c. What information will you gather from them?
- [printout/file to me by TBD #2] Complete dataset
- [draft to me by TBD #2] Describe your data, graphically & numerically, in ways relevant to your questions.
- [final report to me by 4pm on May 13] Draw conclusions from your data.
a. Provide appropriate confidence intervals.
b. Conduct appropriate tests of hypotheses.
c. Assess the appropriateness of your methods to your data.
- [also in final report to me by 4pm on May 13] Discuss your conclusions.
a. What implications do they have for your original questions?
b. Are there aspects of your work that could have been improved?
c. Is there subsequent work you could recommend be done?
- [TBD] Present your findings to your classmates.
Caution: Any project which entails gathering data on HUMAN SUBJECTS must be approved by Taylor’s IRB. Please see me for information about the approval process/contacts after you consult the IRB webpage:
http://online.tayloru.edu/Admin/IRB/
a couple of past projects: [LINK for reports on course webpage]
1. Student Opinions on Changes in the LTC (needed IRB approval)
2. Relationship between NBA players’ heights and their scoring/rebounds (did not need IRB approval)
Project Expectations
See the Project Rubric at this LINK for specific information on how your report will be scored.
o 1-page report from each student, as a separate item, about your roles and contributions AND your assessment of your teammates’ roles and contributions
REMIND ME AND I’LL GENERATE SUCH A FORM FOR YOU.
o presentation) about 30 minutes with about 5 minutes reserved for questions
§ use visual aids (overheads, powerpoint, projector)
o team report
1. objectives
2. how data were gathered
3. descriptive statistics
a. graphs
b. numerical measures
4. inferences
a. check conditions
b. test hypotheses as relevant
c. calculate confidence intervals as relevant
5. draw conclusions (in context) and discuss implications
6. assess weaknesses ; discuss opportunities for further work
7. APPENDIX:
a. Put list of data here.
b. Give detailed calculations for testing & confidence intervals here.
o Grading:
o Report is primary.
o Individual contributions will be important.
o Presentation will play a role too.
[1]1 Common knowledge means any knowledge or facts that could be found in multiple places or as defined by a discipline, department, or faculty member.