MATH3342 -- Engineering Statistics

Spring 2016

Instructor: Josh Engwer

"Mathematics, you see, is not a spectator sport." -- George Polya, circa 1969.

Course Materials:

J.L. Devore, Probability and Statistics for Engineers and the Sciences, 7th Ed, Cengage, 2009.
R.L. Wasserstein, N.A. Lazar, "The ASA Statement on p-Values: Context, Process, and Purpose", The American Statistician, 70 (2016), 129-133.
J.L. Rodgers, "Degrees of Freedom at the Start of the Second 100 Years: A Pedagogical Treatise", Advances in Methods and Practices in Psychological Science, 2 (2019), 396-405.
H.M. Walker, "Degrees of Freedom", Journal of Educational Psychology, 31 (1940), 253-269.
E. O'Brien, "Venn Diagrams for 4 Sets", October 2002.
- Understand why a 4-set Venn diagram made from four circles is non-conforming.
- Focus on the illustrations of 4-set conforming Venn diagrams made from:
  - Four congruent ellipses
  - Four non-congruent rectangles
  - Two non-congruent circles and two congruent beans
F. Ruskey, "A Survey of Venn Diagrams", The Electronic Journal of Combinatorics, March 2001.
- Focus on the illustrations of John Venn's {2,3,4,5,6}-set conforming Venn diagrams.
- Focus on the illustrations of A.W.F. Edwards' {2,3,4,5,6}-set conforming Venn diagrams.
- Focus on the illustration of a 4-set non-conforming Venn diagram made from 4 congruent equilateral triangles.
- Understand the 'Prime Symmetric Venn Diagram Theorem' statement.
- Focus on the illustrations of {5,7,11}-set symmetric conforming Venn diagrams.
M. Haahr, RANDOM.ORG

Course Calendar:

(DEMOS) -- Visual Demonstrations of Key Concepts. Requires the free Wolfram CDF Player.

DATE:		OUTLINES:	SLIDES:	DEMOS:	NOTES:	DESCRIPTION:
01/22	Fri	1.1	1.1			Overview of Engineering Statistics: Data, Samples, Populations
01/25	Mon	1.2	1.2		[EX 1.2.{1,2,3} SOLUTIONS]	Descriptive Statistics: Freq. Tables, Histograms, Modality, Skewness, Outliers
01/27	Wed	1.3	1.3		[EX 1.3.{1,2} SOLUTIONS]	Descriptive Statistics: (Trimmed) Mean, Median, Percentiles, Quartiles, Hinges
01/29	Fri	1.4	1.4		[EX 1.4.1 SOLUTIONS]	Descriptive Statistics: Range, Variance, Std Dev, IHR, IQR, Boxplots
02/01	Mon	2.1	2.1		[EX 2.1.2 SOLUTIONS]	Probability: Sets, Sequences, Sample Spaces, Outcomes, Events
02/03	Wed	2.2	2.2		[EX 2.2.{1,2} SOLUTIONS]	Probability: Axioms, Properties, Interpretations
02/05	Fri	2.3	2.3		[EX 2.3.{1,3,4,6} SOLUTIONS]	Probability: Multi-Stage Experiments, Tuples, Permutations, Combinations
02/08	Mon	2.4	2.4		[EX 2.4.{1,2,3} SOLUTIONS]	Probability: Conditioning, Partitions, Law of Total Probability, Bayes' Theorem
02/10	Wed	2.5	2.5		[EX 2.5.{1,2} SOLUTIONS]	Probability: Independence of Events
02/11	Thurs	********	********	********	Time: 7pm - 11pm Location: MATH 014	LAST-MINUTE HELP SESSION FOR EXAM 1
02/12	Fri	********	********	********	EXAM 1 Info/Logistics/Advice	EXAM 1
02/15	Mon	3.1	3.1		[EX 3.1.{1,2} SOLUTIONS]	Random Variables (rv's): Definition, Examples
02/17	Wed	3.2	3.2		[EX 3.2.{1-6} SOLUTIONS]	Discrete Random Variables: pmf's, cdf's, Probability
02/19	Fri	3.3	3.3		[EX 3.3.{1,2,3} SOLUTIONS]	Discrete Random Variables: Expectation, Variance, Std Dev
02/22	Mon	3.4	3.4		[EX 3.4.1 SOLUTIONS]	Discrete Random Variables: Bernoulli rv's, Binomial rv's
02/24	Wed	3.6	3.6		[EX 3.6.{1,2,3} SOLUTIONS]	Discrete Random Variables: Poisson rv's
02/26	Fri	4.1	4.1		[EX 4.1.{1,2,3} SOLUTIONS]	Continuous Random Variables: pdf's, Probability
02/29	Mon	4.2	4.2			Continuous Random Variables: cdf's, Expectation, Variance, Std Dev
03/02	Wed	4.2	4.2		[EX 4.2.{1,2,3,4} SOLUTIONS]	Continuous Random Variables: cdf's, Median, Percentiles
03/04	Fri	4.3	4.3		[EX 4.3.{1,2,3} SOLUTIONS]	Continuous Random Variables: Uniform rv's, Normal rv's, Std Normal Dist.
03/07	Mon	4.4	4.4		[EX 4.4.{1,2} SOLUTIONS]	Continuous Random Variables: Exponential rv's, Gamma rv's
03/09	Wed	********	********	********		REVIEW FOR EXAM 2
03/10	Thurs	********	********	********	Time: 7pm - 11pm Location: MATH 015	LAST-MINUTE HELP SESSION FOR EXAM 2
03/11	Fri	********	********	********	EXAM 2 Info/Logistics/Advice	EXAM 2
03/14	Mon	********	********	********	SPRING BREAK	<< NO CLASS >>
03/16	Wed	********	********	********	SPRING BREAK	<< NO CLASS >>
03/18	Fri	********	********	********	SPRING BREAK	<< NO CLASS >>
03/21	Mon	5.3	5.3		[EX 5.3.{1,2,3} SOLUTIONS]	Random Samples: iid, Statistics, Sampling Distributions
03/23	Wed	5.4	5.4		[EX 5.4.{1,2,3,4} SOLUTIONS]	Asymptotics: Central Limit Theorem, Normal Approx. to Binomial & Poisson
03/25	Fri	6.1	6.1		[EX 6.1.{1,2,3,4} SOLUTIONS]	Point Estimation: Point Estimators, Unbiased Estimators, Standard Error Point Estimation: Uniformly Minimum-Variance Unbiased Estimators (UMVUE's)
03/28	Mon	********	********	********		<< NO CLASS >>
03/30	Wed	7.1	7.1	7.1		1-Sample Inference: Overview of Confidence Intervals (CI's)
04/01	Fri	7.2	7.2		[EX 7.2.{1,2} SOLUTIONS]	1-Sample Inference: Large-Sample z-CI's for Any Population Mean (σ unknown) 1-Sample Inference: Wilson Score CI's for Any Population Proportion
04/04	Mon	7.3	7.3	7.3	[EX 7.3.1 SOLUTIONS]	1-Sample Inference: Gosset's t Distribution 1-Sample Inference: Small-Sample t-CI's for a Normal Pop. Mean (σ unknown)
04/06	Wed	7.4	7.4	7.4	[EX 7.4.1 SOLUTIONS]	1-Sample Inference: Helmert's Distribution 1-Sample Inference: -CI's for a Normal Population Variance/Std Dev
04/08	Fri	8.1	8.1			1-Sample Inference: Intro to Hypothesis Tests, Type I/II Errors, P-values, α-levels
04/11	Mon	8.2	8.2		[EX 8.2.{1,2,3} SOLUTIONS]	1-Sample Inference: Large-Sample z-Tests about Any Population Mean (σ unknown)
04/13	Wed	8.3	8.3		[EX 8.3.{1,2,3} SOLUTIONS]	1-Sample Inference: Small-Sample t-Tests about a Normal Pop. Mean (σ unknown)
04/15	Fri	8.4	8.4		[EX 8.4.{1,2} SOLUTIONS]	1-Sample Inference: Large-Sample z-Tests about a Population Proportion
04/18	Mon	***	8.5			1-Sample Inference: Statistical Significance vs. Practical Significance 1-Sample Inference: Power Function of a Hypothesis Test
04/20	Wed	********	********	********		REVIEW FOR EXAM 3
04/21	Thurs	********	********	********	Time: 7pm - 11pm Location: MATH 014	LAST-MINUTE HELP SESSION FOR EXAM 3
04/22	Fri	********	********	********	EXAM 3 Info/Logistics/Advice	EXAM 3
04/25	Mon	9.1	9.1		[EX 9.1.1 SOLUTIONS]	2-Sample Inference: Large-Sample z-Tests & z-CI's for Any Two Pop. Means
04/27	Wed	9.2	9.2		[EX 9.2.1 SOLUTIONS]	2-Sample Inference: Small-Sample t-Tests & t-CI's for Two Normal Means
04/29	Fri	9.4	9.4		[EX 9.4.1 SOLUTIONS]	2-Sample Inference: Large-Sample z-Tests & z-CI's for Two Population Proportions
05/02	Mon	* *	3.5 4.5			Discrete Random Variables: Geometric rv's, Negative Binomial rv's Continuous Random Variables: Lognormal rv's, Weibull rv's, Beta rv's
05/04	Wed	********	********	********		REVIEW FOR FINAL EXAM
05/06	Fri	********	********	********		REVIEW FOR FINAL EXAM
05/09	Mon	********	********	********		REVIEW FOR FINAL EXAM
05/13	Fri	********	********	********	EXTENDED OFFICE HOURS: 8:30am - 3:00pm	EXTENDED OFFICE HOURS
05/16	Mon	********	********	********	FINAL EXAM Info/Logistics/Advice	FINAL EXAM

Back to Courses

Best viewed at 1280x720 (720p) screen resolution or higher.