Stat 360 (formerly Math 360) sections 0 and 1: Statistical Methods

Prof. Andrew Ross

Fall Semester 2016

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We believe that the RELATIONSHIPS we have and those we continue to develop will support us as we learn and grow together as a community.

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Basic Information


This version posted on: 2016-08-30

General Description

This is an introductory but calculus-based statistics course, often taken by students from affiliated disciplines. We aim to keep our eye on the big ideas of statistics: Distribution, Inference, Model, Sample, and Variation. 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)." http://cbmsweb.org/MET_Document/index.htm

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.

Prerequisites

Math 120 (Calculus I)

Follow-up courses:

MATH 419W - Introduction to Stochastic Mathematical Modeling (Gen Ed Area I, W)
ECON 415 - Introduction to Econometrics
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 Meetings

 
MW 12:30-1:45 Stat 360-0, PH 305, CRN 16762
TR 12:30-1:45 Stat 360-1, PH 305, CRN 16764

Mon/Wed Daily Schedule

ABCDEFGHI
1
Stat 360-0Prof. Andrew Ross; MW 12:30-1:45 ; Pray-Harrold 305CRN 16762
2
Class#Date 2016dayunitTopicRequired Additional ReadingHW AssignedHW DueBonus Tech Material after class
3
19/7Wed1Intro; randomization example; car-insurance advertising; population vs sample, types of datam360-ch01-data-types.docxCh 1 preview* = deviation from usual 7-day delaytext-to-columns
4
29/12Mon1;2Discrete vs Continuous; PivotTables, Bar charts, Dotplots; Ch 2 BiasCh 1Pivot Tables
5
39/14Wed2Random vs Stratified Samples, etc; Random Rectangles activitym360-ch02.2-2.3-powerpoint.pptxCh 2a; 2bCh 1*left/mid/right and =DATE
6
49/19Mon3Graphical Methods for Describing DataCh 3Ch 2a*Kernel Density Estimates (KDEs)
7
59/21Wed4Center, Variability, Boxplots, Empirical Rule, z-scores, Percentiles & Plotsm360-ch04-notes.docxCh 4a and 4bCh 2bMarked Scatterplots
8
69/26Mon5Correlation; RegressionCh 5aCh 3plot the percentile curve; dotplot-histogram-crf-etc
9
79/28Wed5Assessing fit; Nonlinear Relationships and Transformations5b previewCh 4a and 4bvlookup
10
810/3Mon55 wrapupCh 5bCh 5aSolver for nonlinear regression
11
910/5Wed6Definition and Properties of Prob; Conditional Probability; independence, PIE, Bayes, Prob via Simulationm360-ch06a-powerpoint.pptx
and
m360-ch06-bayes-table-handout.docx
Ch 6ambulance travel distance simulation
12
1010/10Mon7Random Variables; Discrete and Continuous Distributions; Mean and StdDev; linear functions and sumsm360-ch07a-notes.docxCh 7aCh 5bsumproduct
13
1110/12Wed7Binomial, Geometric; Normal; Checking and Transformations for Normality; Binom~Normal; QQm360-ch07b-notes.docxCh 7bCh 6dotplot-histogram-crf-qq
14
1210/17Mon8Statistics and Sampling Variability; Sampling Distribution of a Mean8 previewCh 7aWhat-If Data Tables, 1-dim
15
1310/19Wed8Central Limit Theorem; Sampling Distribution of a ProportionCh 8Ch 7bWhat-If Data Tables, 2-dim
16
1410/24Mon9Point Estimation; Confidence Interval for a ProportionCh 9aconditional formatting
17
1510/26Wed9Confidence Interval for a Mean (incl. t-distrib)Ch 9bCh 8sparklines
18
1610/31MonmidtermmidtermCh 9aparallel axis plots
19
1711/2Wed10Hypotheses and Test Procedures; Errors in Hypothesis Testing; Proportionm360-ch10a-powerpoint.pptxCh 10aCh 9bcountif, sumif, averageif
20
1811/7Mon10Hypothesis Tests for Population Mean; Power and Probability of Type II errorCh 10b; midterm corrections
21
1911/9Wed112-sample t-test for means (indep); 2-sample t-test for means (paired); skipping 2-proportionsCh 11Ch 10a
22
2011/14Mon12Categorical Association part ahandoutCh 12a; ProposalCh 10bPivot Tables
23
2111/16Wed12Categorical Association part bhandoutCh 12bCh 11; midterm corrections
24
2211/21Mon12Categorical Association part chandoutCh 12cCh 12a; ProposalPasting into Word/ ppt: live or dead copies?
25
2311/28Mon13Linear Regression and Correlation: Inferential Methodsm360-ch13-notes.docxCh 13Ch 12bExcel Regression Tool
26
2411/30WedcalcMultiple Testing; Regression to the Mean; Covariance; calculus-based methodsm360-ch99-calculus-supplement-v2.docxCh 12cLiveRegression
27
2512/5MoncalcCalculus-based methods; Poisson Processesch99calcCh 13What-If Goal Seek
28
2612/7WedReview Daych999datafestFinal Report
29
2712/12Monpresent.PresentationsPresentation
30
2812/14WedFinal360-0 final: Wed Dec 14, 11:30 (AN HOUR EARLY)ch99calc and ch999datafest
31
2912/19Monno class--other classes having finals

Tue/Thu Daily Schedule

ABCDEFGHI
1
Stat 360-1Prof. Andrew Ross; TR 12:30-1:45 PH 305CRN 16764
2
Class#Date 2016dayunitTopicRequired Additional ReadingHW AssignedHW DueBonus Tech Material after class
3
19/8Thu1Intro; randomization example; car-insurance advertising; population vs sample, types of datam360-ch01-data-types.docxCh 1 preview* = deviation from usual 7-day delaytext-to-columns
4
29/13Tue1;2Discrete vs Continuous; PivotTables, Bar charts, Dotplots; Ch 2 BiasCh 1Pivot Tables
5
39/15Thu2Random vs Stratified Samples, etc; Random Rectangles activitym360-ch02.2-2.3-powerpoint.pptxCh 2a; 2bCh 1*left/mid/right and =DATE
6
49/20Tue3Graphical Methods for Describing DataCh 3Ch 2a*Kernel Density Estimates (KDEs)
7
59/22Thu4Center, Variability, Boxplots, Empirical Rule, z-scores, Percentiles & Plotsm360-ch04-notes.docxCh 4a and 4bCh 2bMarked Scatterplots
8
69/27Tue5Correlation; RegressionCh 5aCh 3plot the percentile curve; dotplot-histogram-crf-etc
9
79/29Thu5Assessing fit; Nonlinear Relationships and Transformations5b previewCh 4a and 4bvlookup
10
810/4Tue55 wrapupCh 5bCh 5aSolver for nonlinear regression
11
910/6Thu6Definition and Properties of Prob; Conditional Probability; independence, PIE, Bayes, Prob via Simulationm360-ch06a-powerpoint.pptx
and
m360-ch06-bayes-table-handout.docx
Ch 6ambulance travel distance simulation
12
1010/11Tue7Random Variables; Discrete and Continuous Distributions; Mean and StdDev; linear functions and sumsm360-ch07a-notes.docxCh 7aCh 5bsumproduct
13
1110/13Thu7Binomial, Geometric; Normal; Checking and Transformations for Normality; Binom~Normal; QQm360-ch07b-notes.docxCh 7bCh 6dotplot-histogram-crf-qq
14
1210/18Tue8Statistics and Sampling Variability; Sampling Distribution of a Mean8 previewCh 7aWhat-If Data Tables, 1-dim
15
1310/20Thu8Central Limit Theorem; Sampling Distribution of a ProportionCh 8Ch 7bWhat-If Data Tables, 2-dim
16
1410/25Tue9Point Estimation; Confidence Interval for a ProportionCh 9aconditional formatting
17
1510/27Thu9Confidence Interval for a Mean (incl. t-distrib)Ch 9bCh 8sparklines
18
1611/1TuemidtermmidtermCh 9aparallel axis plots
19
1711/3Thu10Hypotheses and Test Procedures; Errors in Hypothesis Testing; Proportionm360-ch10a-powerpoint.pptxCh 10aCh 9bcountif, sumif, averageif
20
1811/8Tue10Hypothesis Tests for Population Mean; Power and Probability of Type II errorCh 10b; midterm corrections
21
1911/10Thu112-sample t-test for means (indep); 2-sample t-test for means (paired); skipping 2-proportionsexample Proposals and ReportsCh 11Ch 10a
22
2011/15Tue12Categorical Association part ahandoutCh 12a; ProposalCh 10bPivot Tables
23
2111/17Thu12Categorical Association part bhandoutCh 12bCh 11; midterm corrections
24
2211/22Tue12Categorical Association part chandoutCh 12cCh 12a; ProposalPasting into Word/ ppt: live or dead copies?
25
2311/29Tue13Linear Regression and Correlation: Inferential Methodsm360-ch13-notes.docxCh 13Ch 12bExcel Regression Tool
26
2412/1ThucalcMultiple Testing; Regression to the Mean; Covariance; calculus-based methodsm360-ch99-calculus-supplement-v2.docxCh 12cLiveRegression
27
2512/6TuecalcCalculus-based methods; Poisson Processesch99calcCh 13What-If Goal Seek
28
2612/8ThuReview Day; presentation tipsexample Presentationsch999datafestFinal Report
29
2712/13Tuepresent.Presentations (T/R class has presentations first)Presentation
30
2812/15Thuno class--other classes having final examsch99calc
31
2912/20TueFinal360-1 final: Tue Dec 20, 11:30 (AN HOUR EARLY)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
andrew.ross@emich.edu
http://people.emich.edu/aross15/
(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.
Mon/Wed
 10:00-11:00 Office Hours
 11:00-12:15 Math 319, PH 521
 12:30-1:45 Stat 360-0, PH 305
  1:45-2:45 Office Hours
  3:30- 4:30 (Wed) faculty research meeting
  4:30- 5:00 (Wed) student research meeting
Tue/Thu
 11:30-12:30 Office Hours
 12:30-1:45 Stat 360-1, PH 305
  1:45-2:45 Office Hours 
  4:30-5:30 Office Hours
  5:30-6:45 Math 560, PH 503

Fri:
	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:

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

Attendance

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.

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

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.

Exams

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

Project

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 system 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 and consult with me during office hours to ensure you know the material.

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. Students should bring a draft of what they're working on and their assignment sheet. The UWC opens for the Winter 2013 semester on Monday, January 14 and will close on Friday, April 19.

The UWC also offers small group workshops on various topics related to writing (e.g., Organizing Your Writing; Incorporating Evidence; Revising Your Writing; Conquering Commas; Finding and Fixing Errors). Workshops are offered at different times in the UWC. Visit the UWC page ( http://www.emich.edu/english/writing-center ) to see our workshop calendar. To register for a workshop, click the link from the UWC page for the type of workshop you wish to attend.

The UWC also has several satellite sites across campus. These satellites provide writing support to students within the various colleges. For more information about our satellite locations and hours, visit the UWC web site: http://www.emich.edu/english/writing-center .

The Academic Projects Center (116 Halle Library) also offers one-to-one writing consulting for students, in addition to consulting on research and technology-related issues. The APC is open 11 a.m. to 5 p.m. Mondays through Thursdays for drop-in consultations . Additional information about the APC can be found at http://www.emich.edu/apc . Students visiting the Academic Projects Center or any of the satellites of the University Writing Center should also bring with them a draft of what they're working on and their assignment sheet.

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, emu_ombuds@emich.edu, or visit the website: www.emich.edu/ombuds