8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Instructors: Jim Litster, Joseph Irudayaraj, Patrick Oglesby

Teaching Assistant: Laura Hirshfield, Harshit Sodhani, Hector

ChangSecretary: Virginia Ewing FRNY 1060A

vewing@purdue.edu

CHE32000

Statistical Modeling and QualityEnhancement

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Does the increase of CO2 in the

atmosphere cause global warming?

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Does the increase of CO2 in the

atmosphere cause global warming?

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Our conclusion is made difficult because:

All real data contains variability

 ± In the math world

Y = 10

 ± In the CHE205 world

Y = 10 kg

 ± In the real world

Y = 10±2 kg

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Our conclusion is made difficult because:

All real data contains variability

 ± In the math world

Y = 10

 ±In the CHE205 world

Y = 10 kg

 ± In the real world

Y = 10±2 kg

A random variable has a measured value that changesfrom one replicate to another.

X = +

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Our conclusion is made difficult because:

We did not have a desi gned  experiment.

Three types of experiment

 ±Retrospective study

 ± Observational study

 ± Designed experiment

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

The Engineering Method

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Stat ist ics is the science of d ata

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Statistical Inference

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Course Objective

Develop and apply statistical methods for use

in the senior engineering laboratories and for

professional use in the chemical process

industries. ± How to handle the variability in real data

 ± How to estimate, measure and minimize

experimental error

 ± How to test statistical hypothesis on real data

 ± Developing models to fit real data

 ± Designing useful experiments

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Course structure

2 lectures per week ± Key concepts

 ± Some examples

 ± Handouts to be posted on blackboard. Bring them to class.

Weekly recitations ± Very important

 ± Applications and Problem solving ± By hand

 ± Using computer software

Text book Montgomery, Runger and Hubele: E ngi neeri ng Stat ist ics 5th E d 

Also resources on the web pagewww.wiley.com/college/montgomery

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Course structure

Blackboard site

 ± Resources for lectures

 ± Homeworks and solutions

 ± Other resources

 ± Grades

 ± Check at least once a week

Assessment

 ± Exams during semester: two @ 15%

 ± final exam 30%

 ± Recitation/homeworks 20%

 ±

Project(s) 20%

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

Recitations and homeworks

Recitations start this week

 ± Grade for active attendance

 ±

Homeworks done in groups of 3 ± Groups assigned randomly in your recitation group

this week

 ± One grade per group + peer assessment

 ± First homework in week 2

8/3/2019 CHE320 Introductory Lecture

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CHE32000 Statistical Modeling and Quality Enhancement

This week

Attend your recitation

Browse through chapters 1 and 2 of the text

Log on to the text book website and look atthe various on line resources

Download first set of notes and bring them to

W

ednesdays lecture