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    Minitab

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    MINITAB Applications in Six Sigma Agenda 13:00-13:30 Registration 13:30-14:20 MSA-MINITAB 14:20-14:30 Break 14:30-15:20 SPC-MINITAB 15:20-15:30 Break 15:30-16:20 Case study (Healthcare & Banking) 16:20-16:30 Q&A July 14‚ 2006 in Taipei MSA-MINITAB Application in (Measurement Systems Analysis‚ MSA) Measuring System. What is a Measuring System? •The measuring device (Repeatability) •The person who is taking the measurement (Reproducibility) 3 Measurement Process The ideal measurement

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    minitab code

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    MINITAB CODE for Modern Engineering Statistics (1) P. 12 Lag plot commands Such a plot can be produced in MINITAB with the following sequence of commands. MTB>LAG C1 C2 MTB>PLOT C1*C2 (2) P. 13 (Figure 1.5) Code to produce Figure 1.5: MTB >SET C10 DATA> 1:49. DATA>END MTB>SET C1 DATA> ........ DATA>SET C2 DATA> .... .... DATA>END

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    Minitab Tutorial

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    © 2010 by Minitab‚ Inc. All rights reserved. ® ® ® Release 16.1.0 Minitab ‚ the Minitab logo ‚ Quality Companion by Minitab and Quality Trainer by Minitab® are registered trademarks of Minitab‚ Inc. in the United States and other countries. Capability Sixpack™‚ Process Capability Sixpack™‚ ReportPad™‚ and StatGuide™ are all trademarks of Minitab‚ Inc. Six Sigma® is a registered trademark and service mark of Motorola‚ Inc. All other marks referenced remain the property of their respective owners

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    Using MINITAB

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    * Using MINITAB * Graphics * Shapes of Distributions * Descriptive Statistics * Empirical Rule Data in MINITAB * MINITAB is a powerful‚ yet user-friendly‚ data analysis software package. You can launch MINITAB by finding the icon and double clicking on it. After a moment you will see two windows‚ the Session Window in the top half of the screen and the Worksheet or Data Window in the bottom half. * Data have already been formatted and entered into a MINITAB worksheet

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    Data Log(Attendance) = B1wins + B2FCI + B3tktprice + B4payroll + B5state + B6earnspop In order to explain the effect that winnings percentage has on attendance‚ I have created an adjusted economic model that I have specified above. In order to test my economic model‚ I have compiled data for each of the variables specified in the model from the years 2003 to 2005. The question that I will be answering in my regression analysis is whether or not wins have an affect on attendance in Major

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    The Shampoo Data Set

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    The Shampoo Data Set This data set is generated by a study of Brand X shampoo. It contains two measurements of customer satisfaction (on a scale from 0 to 100) with a shampoo sample. The customer satisfaction measurements were taken from 10 men and 10 women at two separate times. The first measurement is taken before the presentation of an advertising campaign‚ and the second measurement is taken after the campaign. The last column contains a dichotomous measure of purchase intentions. Each

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    Real Estate Data Set

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    give an educated guess on a linear regression model for pricing real estate using a real facts date set using numbers and facts. Normally two approaches are used for valuing a real estate property: income and sales comparison. The sales assessment approach values a real estate property based on sale prices of similar properties. In this case the properties with familiar individuality are basically on the same price level‚ it would be typical to use a linear regression model to complete this demonstration

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    Minitab Analysis

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    Regression Analysis: IBI versus Area The regression equation is IBI = 52.9 + 0.460 Area Predictor Coef SE Coef T P Constant 52.923 4.484 11.80 0.000 Area 0.4602 0.1347 3.42 0.001 S = 16.5346 R-Sq = 19.9% R-Sq(adj) = 18.2% Analysis of Variance Source DF SS MS F P Regression 1 3189.3 3189.3 11.67 0.001 Residual Error 47 12849.5 273.4 Total 48 16038.8 Unusual Observations Obs Area

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    HW#3 Run regression analysis using the Energy Drinks Data posted on elearning. You can work by yourself‚ or work in a group (up to 5 students per group) and submit one homework per group. 1. (a) Run the linear regression model that express quantity sales (oz) of Full-Throttle as the dependent variable; the list of explanatory variables are price of Full-Throttle‚ the price of Monster‚ price of Red Bull‚ price of Rockstar and customer count. Submit the excel output. What is the R2 value? What

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    Data Will Set You Free

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    Ford CEO Alan Mulally is known for starting meetings by saying “Data will set you free” and for trying to change Ford’s culture to one that is based on increased accountability‚ more information sharing‚ and hard metrics. “You can’t manage a secret‚” he is also fond of saying. Although it’s not clear whether Mulally’s approach will work at Ford‚ which is known for its self-contained fiefdoms where little information is shared‚ some companies have found that managing people according to hard metrics

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