ST 370: Probability and Statistics for Engineers Spring, 2015 TuTh 11:45 am - 1:00 pm, Cox Hall

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1 ST 370: Probability and Statistics for Engineers Spring, 2015 TuTh 11:45 am - 1:00 pm, Cox Hall Instructor: Dr. Zhao-Bang Zeng (szeng@ncsu.edu), 3211C Broughton Hall, (919) (office), (919) (cell) Office Hours: Tuesday/Thursday 1:00-3:00PM, or by appointment Teaching Assistant: Lin Yu (lyu9@ncsu.edu) TA Office Hours: TBA, Tutorial Center in 1101 SAS Hall Course Prerequisite: C or better in MA 241 Course Webpage: Access Moodle Course Page via Materials: Class notes at Wolfware Textbook: D.C. Montgomery and G.C. Runger. Applied Statistics and Probability for Engineers. 5th edition, Wiley, We will cover selected topics in Chapter 1-9, 11, 13, and 14 Reference Text: Stephen Vardeman and J. Marcus Jobe. Basic Engineering Data Collection and Analysis, 2001, Duxbury-Brooks/Cole, ISBN: X WebAssign: Access may be purchased for $19.95 at the book store or on-line at Course objectives*: By the end of the course you should be able to: Construct basic numeric and graphical summaries of data Plan and analyze simple factorial designs Calculate probabilities using basic probability distributions Make inference using basic statistics (See Learning objectives for more detailed information) Calculator: You will need a calculator for this course. Homework: Assignments will be submitted and graded through WebAssign (see above). You will use your unity login and password to access assignments. No late homework assignments will be accepted. Midterm Exams: There will be two midterms (closed book) during the semester. Tables will be provided as necessary. These tests will not be cumulative. You may not use a cell phone, PDA, laptop or any web-enabled device during a test. You may leave the room during a test only in an extreme emergency. The test schedule will be posted later. No post-test make-up tests will be given. If you miss a test, you receive score zero for that test. If you have a conflict with a test, let me know as soon as possible (no later than 2 weeks before the test) and perhaps something can be worked out. If you believe that an error was made in grading your test, you should write a short justification of your claim and attach it to the test. Please note that the entire exam will be re-graded, not just the problem in question to ensure consistency and fairness.

2 Final Exam: The final exam will be cumulative. The basic rules for other exams also hold for the final. The final exam is 8:00-11:00 am on May 5 in the regular class place (00214 Cox Hall). Final Course Grade: Final course grades will be calculated based on the following: Homework 100 points* Midterm points Midterm points Project 75 points Quizzes 25 points** Final Exam 100 points Total 500 points * Twelve 10 points each, with the two lowest homework grades dropped. No make-up allowed. ** Five or more in-class quizzes will be given, with each worth 5 points. The top 5 grades count. This Course uses Standard NCSU Letter Grading: 97 A A < A- < B+ < B < B- < C+ < C < C- < D+ < D < D- < 63 0 F < 60 Quizzes and In-Class Exercises: Quizzes and In-class exercises will be conducted during class time. These activities may not be announced ahead of time and there will be no make-ups. Project: A group project will be assigned. There will be approximately 4 students per group. The project will involve planning, collecting data, and analyzing the results of a two-factor experiment. The intent of the project is to increase your understanding of designing and conducting an experiment with statistical analysis. More details will be given later in the semester. Requirements for Credit-Only (S/U) Grading: In order to receive a grade of S, students are required to take all exams and quizzes, complete all assignments, and earn a grade of C- or better.

3 Conversion from letter grading to credit only (S/U) grading is subject to university deadlines. Refer to the Registration and Records calendar for deadlines related to grading. For more details refer to Requirements for Auditors (AU): Information about and requirements for auditing a course can be found at Policies on Incomplete Grades: If an extended deadline is not authorized by the instructor or department, an unfinished incomplete grade will automatically change to an F after either (a) the end of the next regular semester in which the student is enrolled (not including summer sessions), or (b) the end of 12 months if the student is not enrolled, whichever is shorter. Incompletes that change to F will count as an attempted course on transcripts. The burden of fulfilling an incomplete grade is the responsibility of the student. The university policy on incomplete grades is located at StatCrunch Software: As a registered student at NCSU, you are eligible to use StatCrunch software at no cost Some homework may require the use of software. Attendance and Communication: Students are expected to attend all regularly scheduled meetings of the course. Students are expected to check their NCSU regularly to receive course announcements. The appropriate time to ask for additional explanations of course material or assistance on assignments is during lecture or office hours. Course-related to the instructor or the TAs should be used sparingly and primarily for administrative purposes. For complete attendance and excused absence policies, please see Classroom policies: Courtesy in the classroom is required. Please come on time and do not start packing up before class is over. Please turn off all cell phones before class begins. Please refrain from conversations with your neighbor during class, except when you are instructed to do so during in-class exercises. Attendance is expected and will affect grades through the in-class quizzes. Academic Integrity: Cheating will not be tolerated. See the university s policy on academic integrity athttp:// You may work together on homework assignments, but simply giving or receiving answers to or from another student is cheating. Cheating also includes copying from another student s paper, using unauthorized materials during exams, and falsifying data. Academic Integrity: Students are required to comply with the university policy on academic integrity found in the Code of Student Conduct found athttp://policies.ncsu.edu/policy/pol Any form of academic misconduct is a violation of the Student Code of Conduct and will not be tolerated. Academic misconduct may be defined as "any activity which tends to compromise the academic integrity of the institution, or subvert the educational process". Academic Honesty: See for a detailed explanation

4 of academic honesty. I expect complete honesty in the completion of exams and assignments. Cheating on an exam at the least will result in an F in the course. Students are encouraged to discuss homework problems with each other on the webassign forums; however, submission of the answers must be done independently. Violations of this rule will not be tolerated and will be considered cheating; violators at the least will receive a 0 on the assignment. Honor Pledge: Your submission of a test via webassign and your submission of an assignment via webassign will be considered equivalent to signing the Honor Pledge: "I have neither given nor received unauthorized aid on this test or assignment." 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 at 1900 Student Health Center, Campus Box 7509, , Non-Discrimination Policy: NC State University provides equality of opportunity in education and employment for all students and employees. Accordingly, NC State affirms its commitment to maintain a work environment for all employees and an academic environment for all students that is free from all forms of discrimination. Discrimination based on race, color, religion, creed, sex, national origin, age, disability, veteran status, or sexual orientation is a violation of state and federal law and/or NC State University policy and will not be tolerated. Harassment of any person (either in the form of quid pro quo or creation of a hostile environment) based on race, color, religion, creed, sex, national origin, age, disability, veteran status, or sexual orientation also is a violation of state and federal law and/or NC State University policy and will not be tolerated. Retaliation against any person who complains about discrimination is also prohibited. NC State's policies and regulations covering discrimination, harassment, and retaliation may be accessed at or Any person who feels that he or she has been the subject of prohibited discrimination, harassment, or retaliation should contact the Office for Equal Opportunity (OEO) at Class Evaluations: Online class evaluations will be available for students to complete during the last two weeks of class. Students will receive an message directing them to a website where they can login using their Unity ID and complete evaluations. All evaluations are confidential; instructors will never know how any one student responded to any question, and students will never know the ratings for any particular instructors. Evaluation website: Student help desk: classeval@ncsu.edu.

5 Course Outline: Topic The schedule may be adjusted. Week Weeks 1-2 Introduction, Basic Terminology, Sampling - Chapter 1 Weeks 2-3 Descriptive Statistics - Chapter 6 ( ) Week 4 Designed Experiments - Chapter 13 (13.1, 13.2, 13.4) Weeks 5-6 Factorial Data Analysis - Chapter 14 ( ) Weeks 6-7 ANOVA - Chapter 13 (13.2.2) Weeks 8-9 Regression Analysis - Chapter 11 (11.1, 11.2, 11.8) Weeks Discrete Random Variables - Chapter 3 ( ) Week 12 Continuous Random Variables - Chapter 4 ( ) Week 13 Normal Distribution - Chapter 4 (4.6) Week Sampling Distributions and Confidence Intervals Chapters 7 ( ) & 8 ( ) Week 16 Hypothesis Testing - Chapter 9 ( )

STA2023 Introduction to Statistics (Hybrid) Spring 2013

STA2023 Introduction to Statistics (Hybrid) Spring 2013 Course Description This course introduces the student to the concepts of a statistical design and data analysis with emphasis on introductory descriptive