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統 計 學 ( 二 )
朝陽科技大學工業工程與管理系副教授
洪弘祈
89.02.28
企業與統計之關係
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品質管制
預測統計與市場調查
績效與人事管理
例行報告之方案評估與決策參考
製程改善
研發能力之提昇
產品可靠度
生產管制
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分段主題
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統計之基礎理論與觀念
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基礎統計在品管與製程上之應用(含可靠度)
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進階統計之一 ~ 實驗計劃法與田口式品質工程
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進階統計之二 ~ 反應曲面技術
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進階統計之三 ~ 迴歸分析
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進階統計之四 ~ 時間序列
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進階統計之五 ~ 多變量分析
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數學 Vs. 統計
數
學
統計之基礎理論與觀念
統
計
社會
科學
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1 100

5 500
在統計上未必為真
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24 1

50 2
在統計上未必為假
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THE ENGINEERING METHOD AND
STATISTICAL THINKING
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Engineering or Scientific Method
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Develop a clear and concise description of the
problem.
Identify, at least tentatively, the important factors that
affect this problem or that may play a role in its
solution.
Propose a model for the problem, using scientific or
engineering knowledge of the phenomenon being
studied. State any limitations or assumptions of the
model.
II
Conduct appropriate Statistics
experiments
and collect data to 5
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THE ENGINEERING METHOD AND
STATISTICAL THINKING
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Refine the model on the basis of the observed data.
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Manipulate the model to assist in developing a
solution to the problem.
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Conduct an appropriate experiment to confirm that
the proposed solution to the problem is both effective
and efficient.
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Draw conclusions or make recommendations based
on the problem solution.
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The Engineering or Scientific
Method
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Statistics
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Deals with the collection, presentation, analysis, and the
use of data to make decisions, solve problems, and design
products and processes.
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Describe and understand variability
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Apply statistical thinking
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Find out the sources of variability
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機率 Vs. 統計
母體
母體參數
統計之基礎理論與觀念
抽樣
推論
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樣本
樣本統計量
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統計之專有名詞
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母體(Population)
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樣本(Sample)
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抽樣(Sampling)
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隨機變數(Random Variable)
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參數(Parameter)
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統計量(Statistics)
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Examples
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統計之基礎理論與觀念
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Dot Diagram
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Location and variability
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Sample Mean
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Some Statistical Terms
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Sample and Sampling
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Population
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Population Mean
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Sample Variance
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Sample Standard Deviation
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Sample Variance and Standard Deviation
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Computation of s2

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n
n 2
2
 x x
 x  nx
i
i
s2  i  1
 i 1
n 1
n 1


n
2
 xi  x
s2  i  1

n 1
 n 
  x
n 2  i  1 
 xi 
n
i 1
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n 1
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Some Statistical Terms
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Population Variance
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Population Standard Deviation
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Degrees of Freedom
• independent terms in the equation
• unknown population mean (m), using sample mean instead
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Statistical Thinking
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Which one has the smaller variation?
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Collecting Engineering Data
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observational study
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designed experiment
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hypothesis testing
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Mechanistic and Empirical Model
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Mechanistic Model: built from our underlying knowledge
of the basic physical mechanism.
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Empirical Model: adding the nature variability, or built
from observed data.
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Designing Experimental Investigation
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factorial experiment
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replicates
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interaction
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fractional factorial experiment
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Observing Processes Over Time
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