STAT 110: Introduction to Descriptive Statistics



STAT 509: Statistics for Engineers

Section 002, Fall 2010

Class Meetings: MWF, 2:30 – 3:20 PM, LeConte 210A

Instructor: Dr. Hao Wang Office: LeConte 219B

Grader: Haifeng Wu Office Phone: TBA Mailbox: LeConte 216

E-mail: hao@stat.duke.edu (temporary)

Course Website : stat.duke.edu/~hw27 (temporary, for lecture notes, homework, solutions, etc.)

Office Hours: MW: 3:20 - 5:50 PM or by appointment.

Description: (Prereq: Math 142 or equivalent) Basic probability and statistics with applications and examples in engineering. Elementary probability, random variables and their distributions, random processes, statistical inference, linear regression, correlation and basic design of experiments with application to quality assurance, reliability, and life testing.

Learning Outcomes:

• Understand and be able to correctly use basic statistical terminology.

• Recognize and evaluate variation in data using descriptive statistics, basic parameter estimation and hypothesis testing.

• Compare data sets using descriptive statistics, parameter estimation, hypothesis testing and analysis of variance.

• Recognize and evaluate relationships between two variables using simple linear regression.

• Apply basic 2k design of experiments in order to study and improve engineering processes.

• Understand and be able to apply simple principles of probability, parameter estimation, hypothesis testing, analysis of variance, simple linear regression, and design of experiments to engineering applications.

Textbook: Statistical Methods for Engineers (any Edition, 3rd is the latest) by Geoffrey Vining and Scott M. Kowalski, Thomson, Brooks/Cole, 2006. ISBN: 0-538-73518-X. The text book for this course is highly recommended, but optional.

Calculator: Each student will need a scientific/engineering calculator. Bring your calculator to class.

Cell Phones: They don’t exist. Keep them out of sight and turned off. You may not use a cell phone in place of a calculator in class.

Attendance: It is expected that all students will attend all classes.

Grading: Grading Scale:

Two In-class Midterm 2*20% A 90-100% C 70-76.9%

Homework 20% B+ 87-89.9% D+ 67-69.9%

Warm ups 10%

Comprehensive Final Exam 30% B 80-86.9% D 60-66/9%

TOTAL 100% C+ 77-79.9% F Less than 60%

Details on Graded Assignments:

In-class midterm (2*20%): The two midterms will take place in late September and early November respectively. They will cover all materials through the time of the exams.

Final Exam (30%): The final exam for this course will be comprehensive and will take place on Monday, December 13 - 9:00 a.m.

Homework (20%): There will be regular homework assignments.  Students are expected to read the book and work problems as required to master the material.  Homework will be graded on a ten point scale: 0 meaning that you did not turn in the homework and 10 meaning that you could not have completed the assignment any better. Homework must be legible, include name, and must be stapled to receive credits.

Missing work: Make-ups are not given for missed work except for the final exam. Your final exam grade is substituted for missed work that is excused by the instructor prior to the absence. A grade of zero will be substituted for all other missed work.

Warm ups (10%): There will be a warm-up exercise at the beginning of some class periods. The exercises will cover basic concepts from topics covered previously in class and covered in the readings and homework assigned for that day. Hopefully these will help you see which parts of the material you understand and which need more work. BRING A CALCULATOR!

Graduate Students: Graduate students taking this course will be required to do a project which will be assigned at mid-semester. It will account for 15% of your grade, while Homework will account for 15% of your grade.

Outline of Topics Covered in STAT 509

|Topic |Text Sections |Topic |Text Sections |

|Probability |Section 3.1 |Inference for a Single Mean |Section 4.3 |

|Discrete Random Variables |Sections 3.2, 3.3 (hypergeometric, binomial, |Inference for Variances |Sections 4.8 |

| |Poisson) | | |

|Continuous Random Variables |Section 3.4 (exponential, Uniform) |Inference for two Populations |Sections 4.5, 4.6 |

|Normal Distribution |Section 3.5 |Simple Linear Regression |Sections 6.1, 6.2 |

|Sampling Distributions |Section 3.6, 3.7 |2k Factorial Based Experiments |7.1-7.3 |

|Inference for proportions |Sections 4.1, 4.2, 4.4 | | |

Honor Code:

Students are expected to abide by Carolina Community: Student Handbook & Policy Guide for all work for this course.  Violations of the Standard will result in a failing final grade for this course and will be reported to the Dean of Students for adjudication.  Ignorance of what constitutes academic dishonesty is not a justifiable excuse for violations.

For the in-class exams, students are required to work alone.  For the projects assignments, students may work with others but each student must submit his or her own answers.

 

................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download