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

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'''Instructor:''' <big> Sean Carver, Ph.D., </big> Professorial Lecturer, American University.
 
'''Instructor:''' <big> Sean Carver, Ph.D., </big> Professorial Lecturer, American University.
  
'''Contact''':
+
'''Contact:'''
  
 
* office location: 107 Gray Hall
 
* office location: 107 Gray Hall
 
* email: carver@american.edu
 
* email: carver@american.edu
 
* office phone: 202-885-6629
 
* office phone: 202-885-6629
 +
 +
'''Class time and location:'''
 +
* Monday:  04:00PM 05:15PM,  ANDERSON HALL, Room  B-14
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* Wednesday:  04:00PM 05:00PM,  WARD BUILDING, Room 201
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* Thursday:  04:00PM 05:15PM,  ANDERSON HALL,  Room B-14
  
 
'''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.
 
'''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.

Revision as of 23:07, 11 August 2014

Basic Statistics (Stat 202)

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

Contact:

  • office location: 107 Gray Hall
  • email: carver@american.edu
  • office phone: 202-885-6629

Class time and location:

  • 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

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.

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:

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