【文章內容簡介】 riance case study Break Testing the fittness of a probability distribution Chisquare: a goodness of fit test The KolmogorovSmirnov Test Goodness of fit exercise using dice Result 和 discussion on exercise Lunch Probabilistic 關系 hip of a regression model Fitting model with least square approach Assumptions 和 variance estimator Making inference about the slope Coefficient of Correlation 和 Determination Example of simple linear regression Simple linear regression exercise (using statapult) Break Simple linear regression exercise (con?t) Presentation of results 第二天 wrap up Abcot Day 3: Multiple regression 和 model building Introduction to multiple regression model Building a model Fitting the model with least squares approach Assumptions for model Usefulness of a model Analysis of variance Using the model for estimation 和 prediction Pitfalls in prediction model Break Multiple regression exercise (statapult) Presentation for multiple regression exercise Lunch Qualitative data 和 dummy variables Models with 2 or more quantitative independent variables Testing the model Models with one qualitative independent variable Comparing slopes 和 response curve Break Model building example Stepwise regression – an approach to screen out factors Day 3 wrap up Abcot Day 4: 設計 of Experiment Overview of Experimental Design What is a designed experiment Objective of experimental 設計和 its capability in identifying the effect of factors One factor at a time (OFAT) versus 設計 of experiment (DOE) for modelling Orthogonality 和 its importance to DOE H和 calculation for building simple linear model Type 和 uses of DOE, (. linear screening, linear modelling, 和 nonlinear modelling) OFAT versus DOE 和 its impact in a screening experiment Types of screening DOEs Break Points to note when conducting DOE Screening DOE exercise using statapult Interpretating the screening DOE?s result Lunch Modelling DOE (Full factoria with interactions) Interpreting interaction of factors Pareto of factors significance Graphical interpretation of DOE results 某些 rules of thumb in DOE 實例 of Modelling DOE 和 its analysis Break Modelling DOE exercise with statapult Target practice 和 confirmation run Day 4 wrap up Abcot Day 5: Statistical 流程 Control What is Statistical 流程 Control Control chart – the voice of the 流程 流程 control versus 流程 capability Types of control chart available 和 its application Observing trends for control chart Out of Control reaction Introduction to Xbar R Chart Xbar R Chart example Assignable 和 Chance causes in SPC Rule of thumb for SPC run test Break Xbar R Chart exercise (using Dice) Introduction to Xbar S Chart Implementing Xbar S Chart 為什么 Xbar S Chart ? Introduction to Individual Moving Range Chart Implementing Individual Moving Range Chart 為什么 Xbar S Chart ? Lunch Choosing the subgroup Choosing the correct sample size Sampling frequency Introduction to control charts for attribute data np Charts, p Charts, c Charts, u Charts Break Attribute control chart exercise (paper clip) Out of control not necessarily is bad Day 5 wrap up Abcot Recap of Statistical Terminology Distributions differs in location Distributions differs in spread Distributions differs in shape Normal Distribution 6? 5? 4? 3? 2? 1? 0 1? 2? 3? 4? 5? 6? % % % % 177。 3? variation is called natural tolerance Area under a Normal Distribution Abcot 流程 capability potential, Cp Based on the assumptions that : 1. 流程 is normal Normal Distribution 6? 5? 4? 3? 2? 1? 0 1? 2? 3? 4? 5? 6? Lower Spec Limit LSL Upper Spec Limit USL Specification Center 2. It is a 2sided specification 3. 流程 mean is centered to the device specification Spread in specification Natural tolerance CP = ? USL LSL 6? ? 8? 6? = Abcot 流程 Capability Index, Cpk 1. Based on the assumption that the 流程 is normal 和 in control 2. An index that pare the 流程 center with specification center Normal Distribution 6? 5? 4? 3? 2? 1? 0 1? 2? 3? 4? 5? 6? Lower Spec Limit LSL Upper Spec Limit USL Specification Center Therefore when , Cpk Cp 。 then 流程 is not centered Cpk = Cp 。 then 流程 is centered USL Y 3? Y LSL 3? Cpk = min , Abcot The 流程 of collecting, presenting 和 describing sample data, using graphical 工具和 numbers. ? Pareto Chart ? Population mean ? Histogram ? Population 標準偏差 Descriptive Statistics Estimates for Descriptive Statistics The 流程 of estimating the population parameters from sample(s) that was taken from the population. ? Sample mean, X ? Population mean, m ? Sample 標準偏差 , S ? Population 標準偏差 , ? (when sample size, n 20) ? Estimated 標準偏差 , R/d2 ? Population 標準偏差 , ? (when sample size, n ? 20) Abcot Probability Theory Probability is the chance for an event to occur. ? Statistical dependence / independence ? Posterior probability ? Relative frequency ? Make decision through probability distributions (. Binomial, Poisson, Normal) Central Limit Theorem Regardless the actual distribution of the population, the distribution of the mean for subgroups of sample from that distribution, will be normally distributed with sample mean approximately equal to the population mean. ? Set confidence interval for sample based on normal distribution. ? A basis to pare samples using normal distribution, hence making statistical parison of the actual populations. ? It does not implies that the population is always normally distributed. (Cp, Cpk must always based on th