Difference between revisions of "Syllabus: Stat 202 Fall 2014"

Revision as of 23:52, 11 August 2014

Basic Statistics (Stat 202) Section 004

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

Contact:

• office location: 107 Gray Hall
• email: carver@american.edu
• 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.

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

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

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.

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: