CBEE 213
Process Data Analysis

Spring 2019

Lecture: TR 4-5:50 LINC 210

Instructors
Prof. Milo Koretsky Catherine Mays
Kristal Williams Ryan Cashen
 koretsm@engr.orst.edu cashenr@oregonstate.edu
Help Hours
Monday 4-5 (100 Gleeson)
Tuesday 1-2 (200 Gleeson)
Help Hours
Monday 4-6
100 Gleeson
Help Hours
Tuesday 1-2
Friday 2:30-3:30
200 Gleeson
Help Hours
Monday 4-6
100 Gleeson

 

AIChE Concept Warehouse

General syllabus for course is available here.

Statistical Tables

Page Contents

 

Text

Engineering Statistics, 5th E, Montgomery, Runger, & Hubele, 2011. ISBN : 978-0-470-63147-8


Open Access Text Resources:
Collaborative Statistics (CS)
StatSoft (SS)
Introductory Statistics (IS)
Engineering Stats Handbook (ESH)
Concepts and Applications of Inferential Stats (CAIS)

Optional Text:

Activity Grid:
Week

Topic

Reading Prequiz Handout Studio Homework

Due

Solution

1

Summary statistics, box plots, scatter plots and histograms

Required.
Montgomery: 1.1, 2.1, 2.3 - 2.6
Week 1
Additional:
CS - Chapter 6
IS - Chapter 2
SS - Elementary Concepts

R: Go to Estimation of Mean, Mode, and SD Use the button  new data set to try again. Repeat until you can come close to the values. Following this, answer the Pre-quiz on Concept Warehouse. Week 1 Lecture Notes Studio1

HW#1

4/10

See Week 2 Lecture Notes
2

Probability distributions

Required
Montgomery: 3.1, 3.2, 3.5.1, 3.6.1, 3.8, 3.13
Additional:
Week 2
Distributions
MATLAB text
CS-Chapter 10
CS-8.5,  CS-8.8
CS Chapter 5
T: Go to Histograms and Box Plots. Use the button :new data set' to try again. Repeat until you can match the representations consistently. Following this, answer the pre-quiz on Concept Warehouse.
R: Pre-quiz on Concept Warehouse
Week 2 Lecture Notes
W_2_T.xlsx
Coin Flip MATLAB
Studio 2 HW#2
Normal Distribution

4/17

HW#2Sln
3

Sampling distributions and confidence intervals

Supplemental reading 

Required
Week 3
Lapin 
Additional:
MATLAB text
CS-11.1, CS-11.2, CS-12.1, CS-12.2CS-12.3
T: Read The Lady Tasting Tea and answer the pre-quiz questions on Concept Warehouse
R:Pre-quiz on Concept Warehouse
Week 3 Lecture Notes Studio_3_Data.xls HW#3
HW_3_1.xlsx
Studio_2_Data.xlsx

4/24

HW#3Sln
4

Sampling distributions and confidence intervals 

Hypothesis Testing 

(1 and 2 sample)

Required:
Week 4
Montgomery:  6.1, 6.2.1, 6.2.3, 6.2.4
Additional:
CS-Chapter 13, CS-Chapter 14
T: Pre-Quiz on Concept Warehouse.
R:  Pre-Quiz on Concept Warehouse.
Week 4 Lecture Notes
W_4_R.xlsx
HW#4

Q 1-3 5/3

Q 4 5/6

(changed)

HW#4Sln (P1-3)
HW#4Sln (P4)
5

Linear regession and model fits

Required
Week 5
Montgomery: 6.3.1, 6.4.1
Additional:

CS-Chapter 16,
T: Pre-Quiz on Concept Warehouse.
R:  Pre-Quiz on Concept Warehouse.
Week 5 Lecture Notes
Studio 5


6

Multiple linear and non linear regression

Required
Week 5
T: The Midterm Exam on Tuesday is in Milam 026. No pre-quiz. The midterm study guide  is available here The midterm study guide is available here Sugar Reactor Laboratory Manual HW#5

5/15

HW#5Sln
7

ANOVA

Required
Week 7
Montgomery
T:
pp 272-281
R: pp 281-288
Additional:
CS - Chapter 17
T: Pre-Quiz on Concept Warehouse
R: Pre-Quiz on Concept Warehouse
Week 7 Lecture Notes ANOVA_StatGraph HW#6
concept maps

5/22

HW#6Sln
8

Statistical Process Control

Required
Week 8
StatSoft
NIST SPC
Montgomery
T: pp 439-456,461-464
T: Pre-Quiz on Concept Warehouse
R: Pre-Quiz on Concept Warehouse
Week 8 Lecture Notes SPC Laboratory Manual HW#7
HW#7_4
HW_7.xls

5//30 
4 PM

HW#7Sln
9

DOE

Required
Week 9
Montgomery
T: Sections 7-2 to 7-5
Additional:
StatSoft: DOE Overview
Fractional Factorial Design at 2 levels
A first course in DOE (Chapter 8, pages 165-203)
T: Pre-Quiz on Concept Warehouse
R: Pre-Quiz on Concept Warehouse
Week 9 Lecture Notes
W_9 T.xlsx
W_9 R.xlsx
Studio 9
Fab Link
Equip Manual
Screening Design
HW#8
HW8.xlsx

6/5

HW#8Sln
10 2k Designs
T: Pre-Quiz on Concept Warehouse
R: Pre-Quiz on Concept Warehouse
Week 10 Lecture Notes
The final study guide is available here

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Announcements

  1. Final's week office hours: Thursday June 13, 1-3 PM, 200 Gleeson
  2. Some useful problems from the text have been added to the final study guide.
  3. The final study guide is available here
  4. HW 8 solution posted (06/05)
  5. Week 10 handout posted (06/05)
  6. HW 1-3 regrade request form is here
  7. Final Exam: Friday June 14, 9:30 - 11:20
    Rooms:    
        LINC 210: Sections 12, 14, 16, 18
        LINC 228: Sections 13, 15, 17, 19

    One 8x11" piece of paper with notes only in your own writing, calculator (no graphing calculators), and pencil/pens are permitted.
    Content: Focus on Linear Regression through Design of Experiments
  8. LA Positions for Fall 2019 are available (CBEE 211, ChE 311, ChE 331, CBEE 414, BioE 457, ...). 
  9. HW 7 solutions posted (06/01)
  10. Week 9 lecture notes posted (05/31)
  11. HW 5 and 6 solutions posted (05/29)
  12. Week 8 lecture notes
  13. HW 7 posted (05/20)
  14. Week 7 lecture notes posted
  15. Studio reflections posted here
  16. HW 6 posted (05/14)
  17. HW 5 posted (05/10)
  18. The Midterm Exam on Tuesday is in Milam 026
  19. Error in HW 4 P4 solution has been corrected (5/7)
  20. HW 4 Solutions P 4 is posted (05/06)
  21. HW 4 Solutions P 1-3 is posted (05/05)
  22. Week 5 notes have been posted  (05/03)
  23. Last years midterm is available here
  24. The midterm study guide is available here
  25. Week 4 lecture notes have been posted (04/26)
  26. HW 2 and 3 solutions posted (04/25)
  27. HW 3 posted (04/21)
  28. Weeek 3 lecture notes have been posted (04/19)
  29. HW 3 has been updated for clarification (04/19)
  30. HW 3 Posted (04/16)
  31. Week 2 lecture notes and the MATLAB script from Thursday have been posted (4/16)
  32. HW 2 updated (04/13)
  33. Here is an open source MATLAB text by our own Adam Lambert. 
  34. HW 2 Posted (04/08)
  35. Weeek 1 lecture notes have been posted (04/06)
  36. MATLAB help session will be Monday April 15, 6-7:30 in 200 Gleeson. Please bring a laptop with MATLAB installed. At the help session you will work through the exercise here.
  37. MATLAB syntax sheets are available here and here 
  38. MATLAB resources are available here
  39. HW 1 Posted (04/03/19)
  40. Welcome to ChE, BioE, EnvE 213 :)

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Homework Assignments

The homework assignments will be posted on this web page every week.

Homework grading will be managed via the software program Gradescope. Submit a scanned copy of your HW by 8 AM on  Wed

 

The required format is posted here. Your homework will not be graded if it does not adhere to this format (although we may be lenient for HW1)

Solutions (PDF) will be provided in this page after the date each homework assignment is due.

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Studios

 

Studio Time Section Room GTA LA
W 8 - 10 012 BEXL 102 Catherine Mays Karen DSouza (8-9)
013 BEXL 103 Kristal Williams Anthony Pyka
W 12 - 2 014 BEXL 102 Catherine Mays Ryan McLaughlin
015 BEXL 103 Kristal Williams Karen DSouza
W  2 - 4 016 BEXL 102 Ryan Cashen Shayne Sensenbach
017 BEXL 103 Kristal Williams Ryan McLaughlin
W  4 - 6 018 BEXL 102 Ryan Cashen Shayne Sensenbach
019 BEXL 103 Catherine Mays Anthony Pyka
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Course Learning Objectives

By the end of this course, you will be able to:

  1. By hand and using software, perform the following: (1) statistically summarize data including measures of central tendency and dispersion, and (2) use the appropriate graphical form to summarize data for analysis including box plots, scatter plots and histograms. Match given graphical output to the corresponding summary statistics. Explain trends in data based on these methods.
  2. List the key characteristics of probability distributions, in particular the normal distribution. Given a histogram, explain how it relates to the normal distribution. Given a mean, standard deviation and observed value, calculate the z-score and find the corresponding percentile. Identify populations that follow a binominal distribution and a Poisson distribution
  3. Describe the sampling distribution of a statistic, in particular the t distribution and the chi-squared distribution. Given a study, describe what role statistical inference plays in terms of the population and sample. Calculate confidence intervals. Statistically analyze data for significance and compare sets of data. Perform a hypothesis test to make an assertion about the value of a population parameter (or a comparison between populations), such as the population mean () or variance. Define the standard error of a statistic.
  4. Fit experimental data to an empirical model equation using least squares analysis. For linear regression, both by hand and using software, calculate the slope intercept and correlation coefficient. Explain the relation between the slope of the regression line and the correlation coefficient.
  5. Given data from a process, calculate control limits and capability (Cp and Cpk). Distinguish between specification limits and control limits. Make SPC control charts, including x, x-bar R, and x-bar S charts.
  6. Quantify the effect of (i) a single factor and (ii) two factors on a process by applying Analysis of Variance (ANOVA).
  7. In the context of Design of Experiments (DOE), (i) set up a balanced design array, (ii) create a marginal means plots and/or an interaction plot from the experimental response, and (iii) develop an empirical model equation.
  8. Define the important elements of a measurement system. Calculate the repeatability and reproducibility of a gauge based on measured data.

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Links and Applets

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