Statistical Methods in Quality Management
Date: 2018-10-25 Views: 19

Statistical Methods in Quality Management

Course No.: SMJ2221133    Credit(s): 2

Course Description

This course is based on basic concepts, basic theories and basic methods. Taking the common statistical methods as the center, explain profound the statistical methods of quality management in simple language. This course enables readers not only to know the method, but also to know the theoretical context of the method combining the principles with examples, and highlight the key points of the application of the method, and make the statistical rules followed by random variables easy to understand.

Course Learning Outcomes

After studying the course, students will master all kinds of quality management methods systematically, and understand the statistical ideas contained in various methods and master the different characteristics, application conditions and applicable situations of various quality management methods. Students have the ability to use statistical methods to analyze and solve the actual problems of quality management.

Relationship to Other Courses

The prerequisite for this course is Advanced Mathematics, Linear Algebra.

Textbook and Reading Lists

Textbook:

Jiansi Tie, Statistical Methods in Quality Management. Machinery Industry Press, 2006.

Suggested reading lists:

Jixiang Zhou, Shisong Mao, Statistical Methods for Quality Management. China Statistics Press; 1999.

  

  

Course Assessment

Item

Title

Weighting   (%)

1

Task in home

10%

2

Test and Questions in   class

20%

3

Final Assignment

70%

Course Schedule

Week

Topics

Text

1

Introduction, Quality and Management   and Statistical Methods

Chapters 1

2-3

Data and its Sorting Method

Chapters 2

4 -5

Basis of Statistical Methods

Chapters 3

6-7

Test and Estimation of the   Hypothesis of Measurement Value

Chapters 4

8-9

Test and Estimation of the   Numerical Value Hypothesis

Chapters 5

10-11

Control Chart

Chapters6

12-14

Correlation Analysis and Regression   Analysis

Chapter 7

15-16

Analysis of Variance and Experimental   Design

Chapter 8

17-18

Sampling Inspection

Chapter 9

18

Review