CBEE 213
Process Data Analysis

Spring 2020

Lecture: TR 4-5:50; Studio W 8-9:50, 10-11:50, 12-1:50, 2-3:50, or 4-5:50

We will meet using Zoom; please go to Canvas for Zoom login information

Instructional Team
NameemailHelp Hours
(Go to Canvas Syllabus page for Zoom urls for each help hour)
Milo Koretsky, Instructorkoretskm@engr.orst.edu M 4-6 PM
Di Chen, GTAchend4@oregonstate.eduT 9-11 AM
Juliana Huizenga, GTAhuizengj@oregonstate.eduM 1-3 PM
Omar Mohamed, GTAmohameom@oregonstate.eduT 6-8 PM
Kelly Rodman, GTArodmank@oregonstate.eduM 2-4 PM
Shayne Sensenbach, GTA & LAsensenbs@oregonstate.eduM 3-4 PM , F 12:30-1:30 PM
Tyler Guyer, LAguyert@oregonstate.eduT 8-9 AM; R 12-1 PM
Alekos Hovekamp, LAhovekama@oregonstate.eduM 6-7, T 11-12
Joe Johnson, LAjohnsjo4@oregonstate.eduM 12-1, T 2-3
Kyla Jones, LAjonekyla@oregonstate.eduM 1-2, R 1-2
Jake Cook, Technology Consultationscookjac@oregonstate.eduM 3-4, T 1:30-2:30

 

AIChE Concept Warehouse

General syllabus for course is available here.
Flexibility Request form is available here.

Statistical Tables

Page Contents

 

Texts

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

Statistics for Data Analytics, zyBook


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.
zyBook, Week 1: Exploratory Data Analysis
Week 1 Handout 
Additional:
Montgomery: 1.1, 2.1, 2.3 - 2.6
See also (CS - Chapter 6; IS - Chapter 2; SS - Elementary Concepts)

R: Answer questions in Week 1: zyBook,  Exploratory Data Analysis Week 1 Tuesday Lecture Notes Studio 1

HW#1

4/8

2

Probability distributions

Required
zyBook, Week 1: Normal Distribution
Montgomery: 3.1, 3.2, 3.5.1, 3.6.1, 3.8, 3.13
Week 2
Additional:
Distributions; MATLAB text; CS-Chapter 10
CS-8.5,  CS-8.8, CS Chapter 5
T: Answer questions in Week 2: zyBook,  Normal Distribution
R: Pre-quiz on Concept Warehouse

4/15

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

4/22

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.
4/29
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.


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

5/13

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

5/20

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

5/27

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

6/3

10 2k Designs
T: Pre-Quiz on Concept Warehouse
R: Pre-Quiz on Concept Warehouse

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Announcements

  1. HW 1 posted
  2. Lecture 1 presentation posted 
  3. MATLAB help session will be Saturdat April 11 or Monday April 13 and will be recorded.
  4. MATLAB Textbook is here
  5. MATLAB syntax sheets are available here and here 
  6. MATLAB resources are available here
  7. 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 Zoom Juliana Huizenga
huizengj@oregonstate.edu
Alekos Hovekamp
hovekama@oregonstate.edu
013 Zoom Omar Mohamed
mohameom@oregonstate.edu
Shayne Sensenbach
sensenbs@oregonstate.edu
W 10 - 12020ZoomOmar Mohamed
mohameom@oregonstate.edu
Kyla Jones
jonekyla@oregonstate.edu
W 12 - 2 014 Zoom Kelly Rodman
rodmank@oregonstate.edu
Tyler Guyer
guyert@oregonstate.edu
015 Zoom Di Chen
chend4@oregonstate.edu
Joe Johnson
johnsjo4@oregonstate.edu
W  2 - 4 016 Zoom Juliana Huizenga
huizengj@oregonstate.edu
Alekos Hovekamp
hovekama@oregonstate.edu
017 Zoom Di Chen
chend4@oregonstate.edu
Kyla Jones
jonekyla@oregonstate.edu
W  4 - 6 018 Zoom Kelly Rodman
rodmank@oregonstate.edu
Tyler Guyer
guyert@oregonstate.edu
019 Zoom Shayne Sensenbach
sensenbs@oregonstate.edu
Joe Johnson
johnsjo4@oregonstate.edu
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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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