W2INSE6220

# W2INSE6220 - 1 3 Contents INSE 6220 Week 2 Advanced...

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1 INSE 6220 -- Week 2 Advanced Statistical Approaches to Quality Overview of Course Contents Statistical Methods using MATLAB Statistical Process Control using MATLAB Dr. A. Ben Hamza Concordia University 2 Contents Example 1: Probability of success in test Example 2: Probability of success in test 2 given that test 1<5.5? Descriptive Statistics Probability Distributions Estimation theory Linear Model Non-linear regression Design of experiment Hypothesis testing 3 Contents 0 1 2 3 4 5 6 7 8 9 10 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 Score Density mu=5.72 sigma=1.55 Descriptive Statistics Probability Distributions Estimation theory Linear Model Non-linear regression Design of experiment Hypothesis testing 4 Contents Descriptive Statistics Probability Distributions Estimation theory Linear Model Non-linear regression Design of experiment 5. 6 5. 8 0 1 2 3 4 5 6 7 8 9 10 0 5 10 15 20 25 Score Frequency Hypothesis testing

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5 Contents Example: What is mu and sigma? •Bias •Robustness •Confidence Interval Descriptive Statistics Probability Distributions Estimation theory Linear Model Non-linear regression Design of experiment Hypothesis testing 6 Contents Estimation theory Descriptive Statistics Probability Distributions Linear Model Non-linear regression Design of experiment Hypothesis testing Example 1: When you have less than 4. 5 on test 1, you will not pass Example 2: Average Test1=Average Test 2 7 Contents Descriptive Statistics Probability Distributions Estimation theory Linear Model Non-linear regression Design of experiment Hypothesis testing 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Score Test 1 Score Test 2 8 Contents Descriptive Statistics Probability Distributions Estimation theory Linear Model Non-linear regression Design of experiment Hypothesis testing 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Score Test 1
9 Contents Descriptive Statistics Probability Distributions Estimation theory Linear Model Non-linear regression Design of experiments Hypothesis testing To improve estimate ... To improve prediction of model 10 What is statistics? The science of collecting, organizing, analyzing, and interpreting data in order to make decisions. Methods for processing and analyzing numbers Methods for helping reduce the uncertainty inherent in decision making Why Learn Statistics? So you are able to make better sense of the ubiquitous use of numbers: Business memos Software defect data Quality control Data mining Quality assurance 11 Why Study Statistics? Decision Makers Use Statistics To: Present and describe data and information properly Draw conclusions about large groups of individuals or items, using information collected from subsets of the individuals or items. Make reliable forecasts about a computer software company Predict the number of software defects and Improve software processes What is Data?

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## This note was uploaded on 09/07/2011 for the course INSE 6210 taught by Professor Benhamza during the Fall '10 term at Concordia Canada.

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W2INSE6220 - 1 3 Contents INSE 6220 Week 2 Advanced...

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