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Introduction to Applied Statistics
Decision Sciences and Engineering Systems - DSES-6110

Description
A graduate course in basic statistics. Stresses application to common tasks such as summarizing large databases, making quick estimates, establishing relationships among variables, forecasting, and evaluating alternatives. Topics include probability, common discrete and continuous distributions, sampling, confidence intervals, hypothesis tests, contingency tables, statistical process control, multiple regression analysis. Extensive use of computers to analyze data sets. Students cannot obtain credit for both this course and DSES 4140.

Prerequisites
Calculus and Algebra.

Textbook(s)
Ordering Information

Format
Classes: 14 weeks, 14 sessions
Homework: TBD
Exams: TBD

Grading
Homework: TBD
Exams: TBD

Computing
E-mail and World Wide Web access required for course communications, use of Blackboard, and printing of course notes. Access to a PC with a 486 or higher processor; running under Windows 95/98 or 2000 or Windows NT 4; minimum of 16 MB RAM and 160 MB hard disk space, and CD ROM drive required. Math coprocessor strongly recommended for 486 machines. Use of Minitab or Excel is required.

E-mail access is required for course communications.

Access to Blackboard, Rensselaer's course management tool, is required. Please refer to this page for instructions on how to set up your computer for Blackboard.

Who Should Enroll
This course may be used in your Plan of Study as follows:

Degree Programs
CSCI - elective with advisor pre-approval
CSYS - may be used toward two-course sequence or as elective (both with advisor pre-approval)
ELEC - may be used toward two-course sequence or as elective (both with advisor pre-approval)
EPOW - elective with advisor pre-approval
ITEC - n/a
MANE - elective with advisor pre-approval
MBA - n/a
MGMT-MS - elective with advisor pre-approval
MGTE - required
TCOM – n/a

This course is also open to non-matriculated students who meet the prerequisites and is required for the Certificate in Quality and Reliability.

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