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Course prerequisite: ST371 and corequisite: MA242 Required text: Jay L. Devore (2004). Probability and Statistics for Engineering and the Sciences, 6th Edition. Duxbury Thomson Learning. (ISBN:0534399339) Optional solutions manual: Julie Ann Seely (2004). Student Solutions Manual for Devore's Probability and Statistics for Engineering and the Sciences, 6th Edition. Duxbury Advanced Series. (ISBN:0534399347). Contains worked solutions to the oddnumbered problems. Statistical Resources: Statistical Java Applications Homework: Homework will normally be assigned (as indicated on the homework page) at the end of class each Monday (due on Thursday) and Thursday (due on Monday). Unexcused late homework will not be accepted. The TA will grade only the evennumbered problems, and credit will be assigned for doing the even problems. The final homework average will be computed after dropping the two lowest grades. Examinations: Examinations will be closed book and closed notes. However students will be permitted to bring one 8.5 by 11 inch sheet of notes (both sides) to the midterm exam and two to the final exam. The final exam will be cumulative, but weighted towards the materials covered after the midterm. You must bring calculators to all exams. Exam schedule:
Asking questions: If you have questions about lectures, homework assignments, exams, procedures or any other aspect of
the course please log onto http://courses.ncsu.edu/
, follow the links to "ST" and "ST372" and click on "Message
Board". Then click on "Post New Topic", enter your question
in the Message box, and click on "Submit Message". You will receive a
response from me or another student. Everyone in the class will be able see your
question and the response.
Anonymous mail: If you wish to send me an anonymous suggestion or reminder, send email to st372001sup@wolfware.ncsu.edu. The system will remove mail headers, but you must remember to remove your signature and other identifying information. Grading System: Final grade will be based on: Final Semester Score = (2xHW + 2xM + 3xF)/7 where HW is the homework average (out of 100) after dropping the two lowest scores and M and F are the scores (out of 100) on the midterm and the final exam. Grades will be assigned on the +/ scale. Auditing: Auditors are expected to attend class regularly and submit homework on the same schedule as the other students. The final grade for auditors (AU or NR) will be based on their final homework average. A homework score of 75 or better is required for an AU. Policy on Academic Integrity: The University policy on academic integrity is spelled out in Appendix L of the NCSU Code of Student Conduct. For a more though elaboration see the NCSU Office of Student Conduct website. For this course group work on homework is encouraged. However copying someone else's work and calling them your own is plagiarism, so the work you turn in should be your own. Students with Disabilities: Reasonable accommodations will be made for students with verifiable disabilities. In order to take advantage of available accommodations, students must register with Disability Services for Students (DSS), 1900 Student Health Center, CB# 7509, 5157653. Reference material (Have requested these be on reserve at DH Hill Library): Walpole, R. E., R. H. Myers, S. L. Myers, and K. Ye (2002). Probability and Statistics for Engineers and Scientists,7th Edition. Prentice Hall. Montgomery, D. C. and G. C. Runger (2002). Applied Statistics and Probability for Engineers, 3rd Edition. John Wiley & Sons. Miller, I., R. Johnson, and J. E. Freund (1999). Probability and Statistics for Engineers, 6th Edition. Prentice Hall. Lapin, L. L. (1997). Modern Engineering Statistics. Duxbury Press. 
Course objectives:
This course is the second semester of a twocourse sequence, ST3712, covering probability and statistics. The objective of this course, ST372, is to develop a calculuslevel understanding and working knowledge of statistical inference. The course provides an introduction to the rudiments of statistical inference based on point and interval estimation of population parameters and hypothesis testing including the use of t, chisquare and F. Simple linear regression and correlation analysis will also be introduced. Concepts, methods and applications are emphasized, rather than theory. Successful completion of this course will provide you with a foundation for understanding probabilitybased statistical inference material presented in other courses. Students taking the course will have completed both ST371, and be taking MA242. Syllabus: In ST372 we shall complete chapter 69,12 of the text.
Last updated on: July 03, 2006 