Syllabus: Stat 202 Fall 2014

From Sean_Carver
Revision as of 21:00, 3 December 2014 by Carver (talk | contribs)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

Basic Statistics (Stat 202) Section 004

Instructor: Sean Carver, Ph.D., Professorial Lecturer, American University.


  • office location: 107 Gray Hall
  • email:
  • office phone: 202-885-6629

Office Hours: 107 Gray Hall. Tentatively scheduled as follows: (may be adjusted throughout the semester)

  • 5:30 - 7:00 pm Monday
  • 5:30 - 7:00 pm Tuesday
  • 5:30 - 7:00 pm Wednesday
  • 5:30 - 7:00 pm Thursday.

Tutoring through MATH/STAT tutoring center: Gray Hall, Room 110, Hours:

  • Sunday, 3:00 p.m. to 8:00 p.m.
  • Monday - Thursday, 11:00 a.m. to 8:00 p.m.
  • Friday, 11:00 a.m. to 3:00 p.m.

Class times and locations:

  • Monday: 04:00PM - 05:15PM, ANDERSON HALL, Room B-14
  • Wednesday: 04:00PM - 05:00PM, WARD BUILDING, Room 201
  • Thursday: 04:00PM - 05:15PM, ANDERSON HALL, Room B-14

Important Dates:

  • September 1 (Monday): Labor Day, No Class
  • September 25 (Thursday): EXAM 1, during class, in our classroom
  • October 30 (Thursday): EXAM 2, during class, in our classroom
  • November 26-30 (Wednesday-Sunday): Thanksgiving, No Class
  • December 11 (Thursday), 2:35PM - 5:05PM: FINAL EXAM In SPA Lab (WARD ST-01)

Text: David Moore, George McCabe, and Bruce A. Craig, Introduction to the Practice of Statistics (Seventh Edition), W. H. Freeman and Company.

Software: StatCrunch (web-based software), use this link: For use off campus, set up VPN; see

Course Description (from department website): Data presentation, display, and summary, averages, dispersion, simple linear regression, and correlation, probability, sampling distributions, confidence intervals, and tests of significance. Use of statistical software both to analyze real data and to demonstrate and explore concepts. Four credit hours.

Prerequisite: MATH-15x or higher, or permission of department. No prior knowledge of statistics is assumed.

Learning Outcomes: [Credit Emmanuel Addo, Spring 2013]. By the end of the course, the student should be able to:

  • Use and understand common statistical terminology.
  • Understand data collection methods including designed experiments and sampling methods.
  • Know when to use stemplot, histograms, pie charts, bar charts, and box plots to describe a given distribution.
  • Calculate and interpret the measures of center and spread.
  • Understand the concepts of correlation and linear regression.
  • Understand the concepts of randomness and probability.
  • Understand and interpret probability distributions such as the normal, student's t- and chi-square distributions.
  • State the central limit theorem and understand the concept of a sampling distribution.
  • Calculate confidence intervals for means and proportions--one sample.
  • Use sampling techniques to test hypotheses for means and proportions--one and two samples, contingency table, and goodness-of-fit.

Tentative grading scheme:

Attendance and Participation 10%
Homework 15%
Exam 1 25%
Exam 2 25%
Final 25%

Homework Policy: Will be discussed in class.

Academic Integrity: To the extent that grades are based on a curve, cheating to get a better grade on an assignment or exam can result in lowering the grades of some of your classmates. This is not acceptable and cheating and plagiarism will not be tolerated. As required by American University, I will report all suspected cases of cheating and plagiarism to the Dean's office who will proceed to investigate and adjudicate the issues.

What is considered cheating?

  • Cheating is copying work from another source without giving attribution.
  • Cheating is copying problem(s) from a classmate.
  • It is OK (and, in fact, it is encouraged) to work with other students on homework as long as you write up the solutions yourself and your solutions reflect your own understanding of the problems.
  • When inappropriate copying between students is caught, both parties are culpable.
  • When in doubt, if you are not sure if help you have given or received is appropriate, disclose what you have done. You may not get full credit for the problem but you won't be charged for academic misconduct.