Stat 360 (formerly Math 360) section 0: Statistical Methods

Prof. Andrew Ross

Winter Semester 2017

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Basic Information

This version posted on: 2017-01-01

General Description

In this course you will learn to: This is an introductory but calculus-based statistics course, often taken by students from math-affiliated disciplines. We aim to keep our eye on the big ideas of statistics: Distribution, Inference, Model, Sample, and Variation. There are some skills that most statistics and computer science people should pick up, but that this course doesn't have room for. In particular, the database language SQL is important. So is the ability to use a professional statistics package like "R". This course will, as often optional material, pay particular attention to the need of future math teachers (math-secondary-education majors), as well as math minors and computer science majors. The K-12 Common Core State Standards (CCSS) require much more statistical thinking than previous standards have included.

This course alone will not be enough to prepare you to teach AP Statistics. From an MET draft document: "it is clear that extensive additional preparation in statistics is required to teach AP Statistics. Several graduate courses in statistics are desirable (chosen in individual consultation with faculty in a graduate statistics program). The minimum preparation would be a good lower-level introductory statistics course, based on the sort of textbooks mentioned above, followed by either a second undergraduate statistics course or a graduate statistics course designed for teachers (see the MET Professional Development website for details about such a course)."

Course Catalog Entry

A comprehensive overview of statistical methods and analysis with applications. Topics include descriptive statistics, probability theory, random variables and probability distributions, sampling distributions, estimation and testing hypotheses, correlation and regression, introduction to computer-assisted statistical analysis.


Math 120 (Calculus I)

Follow-up courses:

MATH 419W - Introduction to Stochastic Mathematical Modeling (Gen Ed Area I, W--writing intensive)
ECON 415 - Introduction to Econometrics
STAT 370 - Probability (prerequisite is Calc 3)
STAT 460/576 Applied Survey Sampling
STAT 461/575 Linear Regression Analysis
STAT 462/572 Design and Analysis of Experiments
STAT 468 - Introduction to Biostatistics
STAT 469 - Introduction to Categorical Data Analysis
STAT 474W/574 - Applied Statistics (Gen Ed Area I, W)

STAT 571 Mathematical Statistics I: Probability Theory
STAT 573 Statistical Data Analysis
STAT 577 Applied Multivariate Statistics
STAT 578 Nonparametric Statistics. 

Class Format and Meetings

In-person, not hybrid or online.
Tue/Thu 11:00-12:15 Stat 360-0, PH 405, CRN 26346

Tue/Thu Daily Schedule

  Stat 360-00     Prof. Andrew Ross; TR 11:00-12:15 PH 405   CRN 26346    
Class# Date 2017 day unit Topic Required Additional Reading HW Assigned HW Due Bonus Tech Material after class
1 1/5 Thu 1 Intro; randomization example; car-insurance advertising; population vs sample, types of data m360-ch01-data-types.docx Ch 1 preview * = deviation from usual 7-day delay text-to-columns
2 1/10 Tue 1;2 Discrete vs Continuous; PivotTables, Bar charts, Dotplots; Ch 2 Bias   Ch 1   Pivot Tables
3 1/12 Thu 2 Random vs Stratified Samples, etc; Random Rectangles activity m360-ch02.2-2.3-powerpoint.pptx Ch 2a; 2b Ch 1* left/mid/right and =DATE
4 1/17 Tue 3 Graphical Methods for Describing Data   Ch 3 Ch 2a* Kernel Density Estimates (KDEs)
5 1/19 Thu 4 Center, Variability, Boxplots, Empirical Rule, z-scores, Percentiles & Plots m360-ch04-notes.docx Ch 4a and 4b Ch 2b Marked Scatterplots
6 1/24 Tue 5 Correlation; Regression   Ch 5a Ch 3 plot the pctile curve; dotplot-histogram-crf
7 1/26 Thu 5 Assessing fit; Nonlinear Relationships and Transformations   5b preview Ch 4a and 4b vlookup
8 1/31 Tue 5 5 wrapup   Ch 5b Ch 5a Solver for nonlinear regression
9 2/2 Thu 6 Definition and Properties of Prob; Conditional Probability; independence, PIE, Bayes, Prob via Simulation m360-ch06a-powerpoint,
Ch 6   ambulance travel distance simulation
10 2/7 Tue 7 Random Variables; Discrete and Continuous Distributions; Mean and StdDev; linear functions and sums m360-ch07a-notes.docx Ch 7a Ch 5b sumproduct
11 2/9 Thu 7 Binomial, Geometric; Normal; Checking and Transformations for Normality; Binom~Normal; QQ m360-ch07b-notes.docx Ch 7b Ch 6 dotplot-histogram-crf-qq
12 2/14 Tue 8 Statistics and Sampling Variability; Sampling Distribution of a Mean   8 preview Ch 7a What-If Data Tables, 1-dim
13 2/16 Thu 8 Central Limit Theorem; Sampling Distribution of a Proportion   Ch 8 Ch 7b What-If Data Tables, 2-dim
  2/21 Tue   break week        
  2/23 Thu   break week        
14 2/28 Tue 9 Point Estimation; Confidence Interval for a Proportion   Ch 9a Ch 8 conditional formatting
15 3/2 Thu 9 Confidence Interval for a Mean (incl. t-distrib)   Ch 9b   sparklines
16 3/7 Tue   midterm        
17 3/9 Thu 10 Hypotheses and Test Procedures; Errors in Hypothesis Testing; Proportion m360-ch10a-powerpoint.pptx Ch 10a Ch 9a parallel axis plots
18 3/14 Tue 10 Hypothesis Tests for Population Mean; Power and Probability of Type II error   Ch 10b; midterm corrections Ch 9b countif, sumif, averageif
19 3/16 Thu 11 2-sample t-test for means (indep); 2-sample t-test for means (paired); skipping 2-proportions example Proposals and Reports Ch 11 Ch 10a generating random numbers
20 3/21 Tue 12 Categorical Association part a handout Ch 12a; Proposal Ch 10b Pivot Tables
21 3/23 Thu 12 Categorical Association part b handout Ch 12b Ch 11; midterm corrections  
22 3/28 Tue 12 Categorical Association part c handout Ch 12c Ch 12a; Proposal Pasting into Word/ ppt: live or dead copies?
23 3/30 Thu 13 Linear Regression and Correlation: Inferential Methods m360-ch13-notes.docx Ch 13 Ch 12b Excel Regression Tool
24 4/4 Tue calc Multiple Testing; Regression to the Mean; Covariance; calculus-based methods m360-ch99-calculus-supplement-v4.docx   Ch 12c LiveRegression
25 4/6 Thu calc Calculus-based methods; Poisson Processes   ch99calc Ch 13 What-If Goal Seek
26 4/11 Tue calc Calc, Poisson; presentation tips example Presentations ch999datafest Final Report SQL
27 4/13 Thu   Presentations     Presentation  
28 4/18 Tue   Review day     ch99calc  
  4/20 Thu   Final exam 11:00 a.m. - 12:30 p.m. (usual class time)     ch999datafest  

3 credit hours.

Class meetings will be mostly interactive lectures, with some time to work on problems in class, but hardly ever time to go over problems from the homework; that is best done in office hours or by email before the HW is due.

I expect that you will work on Stat 360 for 6 to 10 hours per week outside of class.

Instructor information

Professor Andrew Ross
Pray-Harrold 515m
(734) 487-1658, but I strongly prefer e-mail instead of phone contact.
Math department main office: Pray-Harrold 515, (734) 487-1444

Office Hours and other help

Here is my complete schedule.
  1:30- 2:00 Office Hours
  2:00- 2:50 Math 121, PH 321 (CRN 20933)
  3:00- 3:30 Office Hours
 10:00-11:00 Office Hours
 11:00-12:15 Stat 360-0, PH 405
 12:15- 1:00 Office Hours, lunch
  1:15- 1:45 faculty research meeting (Thursdays only)
  1:30- 2:00 Office Hours
  2:00- 2:50 Math 121, PH 321 (CRN 20933)
  3:00- 3:30 Office Hours
  5:00- 5:30 Office Hours
  5:30- 6:45 Math 419W/519, PH 324 (CRN 26352/26362)
	no schedule--I'm often on campus, though.
	I have various meetings to go to.
	Send e-mail to make an appointment.

I am also happy to make appointments if you cannot come to the general office hours. Please send me e-mail to arrange an appointment. However, I am not available when I am teaching other classes (see above).

The Mathematics Student Services Center (or "Math Lab") is also here to help you, in Pray-Harrold 411 Their hours are posted here. Please give them a call at 734-487-0983 or just drop by.

Another resource on campus is the Holman Success Center, formerly the Holman Learning Center.

Some assignments in this course will be in the form of papers, which I want to be well written. Please consult with The Writing Center for help in tuning up your writing.

Teaching philosophy, interests

I am a very applied mathematician. Applied, applied, applied. Not pure. Impure. I try to focus on real-world problems, rather than artificial drill problems (though I do recognize the need for some drill). My classes spend much more time on formulating problems (going from the real world to math notation and back) than on proving theorems. If you want the theoretical basis for anything we are discussing, please ask!

My general math interests are in Industrial Engineering and Operations Research (IEOR). In particular, I do research in applied probability and queueing theory, the mathematics of predicting how long it takes to wait in line for service. You can learn more about this in Math 319 and 419W when I teach them. I also enjoy teaching about cost-minimizing/profit-maximizing methods called Non-Linear Programming (NLP) in Math 560, Optimization Theory.

Required materials

Textbook: Introduction to Statistics & Data Analysis, 4th edition, by Peck, Olsen, and Devore amazon link. We do actually use the textbook, fairly heavily in fact. For Fall 2016 and Winter 2017 we will still use the 4th edition; do not buy the 5th edition even if you see it.

This textbook is not calculus-based, but our course is a calculus-based course. So, we will use a calculus-based supplement to the textbook that I have written.

A lot of our work will be done on computers, usually in Excel or a similar spreadsheet. If you had been waiting for a good reason to buy a laptop, this is it. Spreadsheets other than Excel (such as OpenOffice/LibreOffice, Google Docs, etc.) work reasonably well for most things in the class, but some things really don't work well without name-brand Excel. Fortunately, it's available free to EMU students (as of Fall 2016). Email me to ask for details.

Course Web Pages

I will post data files, homework assignment files, etc. on my home page and sometimes only in Canvas

We will use on-line homework submission and gradebook via EMU Canvas to keep track of grades. You are expected to keep an eye on your scores using the system, and get extra help if your scores indicate the need.

Supplementary Materials

You would probably enjoy these books:

Course Content

Course Goals

The objective of this course is to give students an elementary overview of sampling and data analysis using graphical methods, basic probability theory, discrete and continuous random variables, sampling distribution, point and interval estimation, and hypothesis testing. Exposure to computer software, for example, SAS, R or Excel is recommended for statistical analysis purposes.

Grading Policies


Regular attendance is strongly recommended. There will be material presented in class that is not in the textbook, yet will be very useful. Similarly, there are things in the textbook that are might not be covered in class, but are still very useful. If you must miss a class, arrange to get a copy of the notes from someone, and arrange for someone to ask your questions for you. If you are stuck on occasion without your usual child care, you may bring your child to class, and need not even get advanced permission (this is my personal policy--I don't know if EMU has a policy). Please be considerate to your classmates if your child becomes disruptive.

My lectures and discussions mostly use the document camera, along with demonstrations in Excel and other mathematical software. I do not usually have PowerPoint-like presentations, and thus cannot hand out copies of slides.


Homework will be assigned about twice per week, usually 2 assignments per chapter. All homework should be typed and submitted via the Canvas dropbox. The policy is: if it isn't in Canvas, it doesn't exist for grading purposes. Any assignments emailed to me will be treated as drafts, and I will try to respond to them with helpful advice.

I am open to doing contract honors for this class for students in the Honors College. Please contact me if you are interested in doing so.


There will be a midterm exam and a final exam. Quizzes might also occur, announced or not, during the semester.


You will do a project where you create a question, decide how to study it, design a data collection method, collect data, and analyze it. You will write a project proposal so I can be sure you are on the right track, and a final report, which is usually about 5 to 10 pages long. The grade breakdown for the project is roughly:

On average, students should spend a total of about 30 minutes in office hours discussing the project. Plan for this in advance! Teams of 2 are allowed/encouraged, but no team bigger than 2 is allowed.

Overall Grades

There is no systematic grade-dropping method like "lowest 2 scores will be dropped". In the unfortunate event of a need, the appropriate grade or grades might (at the instructor's discretion) be dropped entirely, rather than giving a make-up. You are highly encouraged to still complete the relevant assignments that were dropped, and consult with me during office hours to ensure you know the material. If a student falls hopelessly behind in the homeworks (aside from the project), they may request a grand make-up assignment (which might be done at home or in the math testing room, at the instructor's discretion). This request might or might not be granted, at the instructor's discretion.

Your final score will be computed as follows: Final letter grades will be computed using:
  0 to <48        F
 48 to <52        D-
 52 to <56        D
 56 to <60        D+
 60 to <64        C-
 64 to <68        C
 68 to <72        C+
 72 to <76        B-
 76 to <80        B
 80 to <84        B+
 84 to <88        A-
 88 to <100        A
though if absolutely necessary, a curve might be applied.

General Caveat

The instructor reserves the right to make changes to this syllabus throughout the semester. Notification will be given in class or by e-mail or both. If you miss class, it is your responsibility to find out about syllabus and schedule changes, especially the due dates and times of projects, assignments, or presentations.

Advice from My Other Students

In past years, I've asked my upper-level students to give advice to you, future students, based on their experiences in my courses. Here are some of the highlights:

University Writing Center

The University Writing Center (115 Halle Library; 487-0694) offers one-to-one writing consulting for both undergraduate and graduate students. Students can make appointments or drop in between the hours of 10 a.m. and 6 p.m. Mondays through Thursdays and from 11 a.m. to 4 p.m. on Fridays. The UWC opens for the Winter 2017 semester on Monday, January 9, and will close on Thursday, April 20. Students are encouraged to come to the UWC at any stage of the writing process.

The UWC also has several satellite locations across campus (in Owen, Sill, Marshall, Porter, Pray-Harrold, and Mark Jefferson). These satellites provide drop-in writing support to students in various colleges and programs. The Pray-Harrold UWC satellite (rm. 211) is open Mondays through Thursdays from 11 a.m. to 4 p.m. The locations and hours for the other satellites can be found on the UWC web site:

UWC writing consultants also work in the Academic Projects Center (116 Halle Library), which offers drop-in consulting for students on writing, research, and technology-related issues. The APC is open 10 a.m. to 5 p.m. Mondays through Thursdays. Additional information about the APC can be found at

Students seeking writing support at any location of the University Writing Center should bring a draft of their writing (along with any relevant instructions or rubrics) to work on during the consultation.

Standard University Policies

In addition to the articulated course specific policies and expectations, students are responsible for understanding all applicable University guidelines, policies, and procedures. The EMU Student Handbook is the primary resource provided to students to ensure that they have access to all university policies, support resources, and student's rights and responsibilities. Changes may be made to the EMU Student Handbook whenever necessary, and shall be effective immediately, and/or as of the date on which a policy is formally adopted, and/or on the date specified in the amendment. Please note: Electing not to access the link provided below does not absolve a student of responsibility. For questions about any university policy, procedure, practice, or resource, please contact the Office of the Ombuds: 248 Student Center, 734.487.0074,, or visit the website: CLICK HERE to access the University Course Policies Student Handbook Link: Graduate School Policies:

Food Pantry

Swoop's Pantry (104 Pierce Hall,, 734 487 4173) offers food assistance to all EMU students who could benefit. Students are able to visit twice per month to receive perishable and non-perishable food items, personal hygiene items, baby items, and more. Students can visit our website for hours of operation and more information. If you are in a position to donate to Swoop's, I encourage you to do so!