NATIONAL CHIAO TUNG UNIVERSITY

INSTITUTE OF STATISTICS

 

STATISTICS

FALL 2006

 

 

 


Instructor:

Guan-Hua Huang, Ph.D.

 

Office: 423 Joint Education Hall

 

Phone: 03-513-1334

 

Email: ghuang@stat.nctu.edu.tw

Class meetings:

Monday 15:40-16:30, Thursday 10:10-12:00 at 309 Joint Education Hall

Office hours:

By appointment

Class website:

http://www.stat.nctu.edu.tw/subhtml/source/teachers/ghuang/course/stat06/

 

Credit:

Three (3) credits

 

COURSE SUMMARY

 

The objectives of this course are to

 

           Introduce the basic concepts and methods of statistics with applications in engineering;

           Demonstrate methods of exploring, organizing and presenting data;

           Introduce the fundamentals of probability;

           Present the foundations of statistical inference, including the concepts of parameters and estimates and the use of confidence intervals, and hypothesis tests.

 

Computer software EXCEL will be Introduced and implemented to explore and analyze data.

 

The course consists of lectures and laboratory sessions. The lectures are given on Thursday mornings. The lectures will primarily review and reinforce major issues. There is a laboratory session on Monday afternoon. The laboratory exercise will be distributed prior to each class, and students are expected to read each lab exercise at home. Each student will be assigned to a lab group and discuss the exercise with group members in the lab. At the end of the lab, there will be a seminar-type discussion. Each group is required to hand in a write-up of laboratory problems.

 

HANDOUTS AND TEXTBOOKS

 

Handouts corresponding to each lecture will be available on the class website before each class. The required textbooks for this course are

 

Montgomery, D. C., Runger, G. C., and Hubele, N. F. (2004). Engineering Statistics (3rd Edition), Wiley, New York, NY.

 

王文中 (2004).統計學與EXCEL資料分析之實習應用<第五版>, 博碩文化.

 

The course will follow the content of the first book. The second book is the reference of EXCEL.

 

PREREQUISITES

 

It is assumed students have had calculus and are familiar with matrix and linear algebra. The course does not assume any prior knowledge of statistics or probability.

 

METHOD OF STUDENT EVALUATION

 

The course grade will be based on homeworks (25%), write-ups of lab problems (20%), one midterm exam (25%), and one final exam (30%). The midterm exam will be held on November 9 (10:10-12:00), and the final exam will on January 11 (10:10-12:00).

 

COURSE OUTLINE

 

Readings refer to:

Montgomery, D. C., Runger, G. C., and Hubele, N. F. (2004), Engineering Statistics (3rd Edition), Wiley, New York, NY.

 

Module

Topic

Reading

1

What is statistics?

Chapter 1

2

Data summary and presentation:

a.     Mean, variance

b.     Stem-and-leaf diagram

c.      Histogram

d.     Box plot

e.     Multivariate data

Chapter 2

a.     2-1

b.     2-2

c.      2-3

d.     2-4

e.     2-6

3

Random variables and probability distributions:

a.     Probability and random variables

b.     Discrete random variables

c.      Continuous random variables

d.     Joint distribution and independence

e.     Functions of random variables and Central Limit Theorem

Chapter 3

a.     3-1, 3-2, 3-3

b.     3-7, 3-8, 3-9, 3-10

c.      3-4, 3-5, 3-6

d.     3-11

e.     3-12, 3-13

4

Decision making for a single sample:

a.     Point estimation

b.     Hypothesis testing and

c.      P-value, confidence interval and sample size calculation

d.     Hypothesis testing on mean when variance unknown

e.     Hypothesis testing on proportion

Chapter 4

a.     4-1, 4-2

b.     4-3, 4-4

c.      4-4

 

d.     4-5

e.     4-7, 4-9

5

Decision making for two samples:

a.     Inference on two means when variances known

b.     Inference on two means when variances unknown

c.      Inference on correlated data (paired t-test)

d.     Inference on two proportions

Chapter 5

a.     5-1, 5-2

b.     5-3

c.      5-4

d.     5-6, 5-7

6

Linear models

a.     Simple linear regression

b.     Multiple linear regression

c.      ANOVA

Chapter 6

a.     6-1, 6-2

b.     6-3

c.      Chapter 5: 5-8