This version posted on: 2013-08-27

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

Follow-up courses:

MATH 419W - Introduction to Stochastic Mathematical Modeling (Gen Ed Area I, W) ECON 415 - Introduction to Econometrics MATH 460/576 Applied Survey Sampling MATH 461/575 Linear Regression Analysis MATH 462/572 Design and Analysis of Experiments MATH 468 - Introduction to Biostatistics MATH 469 - Introduction to Categorical Data Analysis MATH 474W/574 - Applied Statistics (Gen Ed Area I, W) MATH 571 Mathematical Statistics I: Probability Theory MATH 573 Statistical Data Analysis MATH 577 Applied Multivariate Statistics MATH 578 Nonparametric Statistics.

Section 0, CRN 11924: Mon/Wed 11:00-12:15 in Pray-Harrold 520 Section 1, CRN 14746: Tue/Thu 11:00-12:15 in Pray-Harrold 520

Brief schedule overview: (for Section 1, the Tuesday/Thursday class, add 1 to each date given)

- Wed Sep 4: First day of our class
- Wed Oct 30: Midterm exam
- Wed Nov 28: Thanksgiving break, no classes
- Wed Dec 4: Proposal due
- Wed Dec 11: Final exam during last ordinary class session
- Tue Dec 17: Final Presentations (instead of exam), usual class time; Project due
- Wed Dec 18: Final Presentations (instead of exam), usual class time; Project due

Class meetings will be mostly interactive lectures, with some time to work on problems in class, and perhaps some time to go over problems from the homework.

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

Mon/Wed: 10:30-11:00 office hours 11:00-12:15 Math 360-0, PH 520 12:15-12:30 office hours and lunch 12:30- 1:20 Math 120-4 (though might slide to 12:45-1:35 ?) 1:30- 2:30 office hours Tue/Thu: 9:00- 9:30 office hours 9:30-10:45 Math 319-0, PH 520 11:00-12:15 Math 360-1, PH 520 12:15-12:30 office hours and lunch 12:30- 1:20 Math 120-4 (though might slide to 12:45-1:35 ?) 1:30- 2:30 office hours 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.

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.

Textbook: Introduction to Statistics & Data Analysis, 4th edition, by Peck, Olsen, and Devore amazon link.

This textbook is not calculus-based, but our course is a calculus-based course. So, I will be writing a calculus-based supplement to the textbook.

A lot of our work will be done on computers. If you had been waiting for a good reason to buy a laptop, this is it.

I will post data files, homework assignment files, etc. on my home page.

We will use on-line homework submission and gradebook via EMU-Online 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.

1 THE ROLE OF STATISTICS AND THE DATA ANALYSIS PROCESS Why Study Statistics The Nature and Role of Variability Statistics and the Data Analysis Process Types of Data and Some Simple Graphical Displays 2 COLLECTING DATA SENSIBLY Statistical Studies: Observation and Experimentation Sampling Simple Comparative Experiments More on Experimental Design More on Observational Studies: Designing Surveys (Optional) Interpreting and Communicating the Results of Statistical Analyses 3 GRAPHICAL METHODS FOR DESCRIBING DATA Displaying Categorical Data: Comparative Bar Charts and Pie Charts Displaying Numerical Data: Stem-and-Leaf Displays Displaying Numerical Data: Frequency Distributions and Histograms Displaying Bivariate Numerical Data Interpreting and Communicating the Results of Statistical Analyses 4 NUMERICAL METHODS FOR DESCRIBING DATA Describing the Center of a Data Set Describing Variability in a Data Set Summarizing a Data Set: Boxplots Interpreting Center and Variability: Chebyshev's Rule, the Empirical Rule, and z Scores Interpreting and Communicating the Results of Statistical Analyses 5 SUMMARIZING BIVARIATE DATA Correlation Linear Regression: Fitting a Line to Bivariate Data Assessing the Fit of a Line Nonlinear Relationships and Transformations Logistic Regression (Optional) Interpreting and Communicating the Results of Statistical Analyses 6 PROBABILITY Chance Experiments and Events Definition of Probability Basic Properties of Probability Conditional Probability Independence Some General Probability Rules Estimating Probabilities Empirically Using Simulation 7 RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS Random Variables Probability Distributions for Discrete Random Variables Probability Distributions for Continuous Random Variables Mean and Standard Deviation of a Random Variable Binomial and Geometric Distributions Normal Distributions Checking for Normality and Normalizing Transformations Using the Normal Distribution to Approximate a Discrete Distribution [ Calculus supplement: x versus X, CDF/PDF and integrals/derivatives, moments, Exponential distribution, misc other distributions, Poisson process] 8 SAMPLING VARIABILITY AND SAMPLING DISTRIBUTION Statistics and Sampling Variability The Sampling Distribution of a Sample Mean (incl Central Limit Thm) The Sampling Distribution of a Sample Proportion 9 ESTIMATION USING A SINGLE SAMPLE Point Estimation Large-Sample Confidence Interval for a Population Proportion Confidence Interval for a Population Mean Interpreting and Communicating the Results of Statistical Analyses 10 HYPOTHESIS TESTING USING A SINGLE SAMPLE Hypotheses and Test Procedures Errors in Hypotheses Testing Large-Sample Hypothesis Tests for a Population Proportion Hypotheses Tests for a Population Mean Power and Probability of Type II Error Interpreting and Communicating the Results of Statistical Analyses 11 COMPARING TWO POPULATIONS OR TREATMENTS Inferences Concerning the Difference Between Two Population or Treatment Means Using Independent Samples Inferences Concerning the Difference Between Two Population or Treatment Means Using Paired Samples Large Sample Inferences Concerning a Difference Between Two Population or Treatment Proportions Interpreting and Communicating the Results of Statistical Analyses 12 THE ANALYSIS OF CATEGORICAL DATA AND GOODNESS-OF-FIT TESTS Chi-Square Tests for Univariate Data Tests for Homogeneity and Independence in a Two-way Table Interpreting and Communicating the Results of Statistical Analyses 13 SIMPLE LINEAR REGRESSION AND CORRELATION: INFERENTIAL METHODS Simple Linear Regression Model Inferences About the Slope of the Population Regression Line Checking Model Adequacy Inferences Based on the Estimated Regression Line (Optional) Inferences About the Population Correlation Coefficient (Optional) Interpreting and Communicating the Results of Statistical Analyses ------------------- The following chapters are parts of the book that we will not have time for: 14 MULTIPLE REGRESSION ANALYSIS Multiple Regression Models Fitting a Model and Assessing Its Utility Inferences Based on an Estimated Model (online) Other Issues in Multiple Regression (online) Interpreting and Communicating the Results of Statistical Analyses (online) Activity 14.1: Exploring the Relationship Between Number of Predictors and Sample Size 15 ANALYSIS OF VARIANCE Single-Factor ANOVA and the F Test Multiple Comparisons The F Test for a Randomized Block Experiment (online) Two-Factor ANOVA (online) Interpreting and Communicating the Results of Statistical Analyses (online) 16 NONPARAMETRIC (DISTRIBUTION-FREE STATISTICAL METHODS (ONLINE) Distribution-Free Procedures for Inferences About a Difference Between Two Population or Treatment Means Using Independent Samples (Optional) Distribution-Free Procedures for Inferences About a Difference Between Two Population or Treatment Means Using Paired Samples Distribution-Free ANOVA

. | 360 ;000;11924;A ;Statistical Methods ;M; ;W | |||

. | 360 ;001;14746;A ;Statistical Methods;T; ;R | |||

. | ||||

. | Date | day | unit | Topic |

. | 2013-09-04 | Wed | 1 | Intro; car-insurance advertising; population vs sample, types of data |

. | 2013-09-06 | Mon | 1;2 | Discrete vs Continuous; Bar charts, Dotplots; Ch 2 Bias |

. | 2013-09-11 | Wed | 2 | Random vs Stratified Samples, etc; Random Rectangles activity |

. | 2013-09-13 | Mon | 3 | Graphical Methods for Describing Data |

. | 2013-09-18 | Wed | 4 | Center, Variability |

. | 2013-09-20 | Mon | 4 | Boxplots, Empirical Rule, Z-Scores, Percentiles |

. | 2013-09-25 | Wed | 5 | Correlation; Regression; |

. | 2013-09-27 | Mon | 5 | Assessing fit; Nonlinear Relationships and Transformations |

. | 2013-10-02 | Wed | 5;6 | 5 wrapup; Ch 6.1: Experiments and Events; Combinatorics |

. | 2013-10-04 | Mon | 6 | Definition and Properties of Prob; Conditional Probability; start Independence (defn, testing P(E|F)=P(E), indep table) |

. | 2013-10-09 | Wed | 6 | Independence: P(E&F)=P(E)P(F); General Rules (PIE, Total Prob, Bayes); prob via simulation |

. | 2013-10-11 | Mon | 7 | Random Variables; Discrete and Continuous Distributions; Mean and StdDev; linear functions and sums |

. | 2013-10-16 | Wed | 7 | Binomial, Geometric; Normal; Checking and Transformations for Normality; Binom~Normal |

. | 2013-10-18 | Mon | 8 | Statistics and Sampling Variability; Sampling Distribution of a Mean |

. | 2013-10-23 | Wed | 8 | Central Limit Theorem; Sampling Distribution of a Proportion |

. | 2013-10-25 | Mon | 9 | Point Estimation; Confidence Interval for a Proportion; |

. | 2013-10-30 | Wed | midterm | midterm |

. | 2013-11-01 | Mon | 9 | Confidence Interval for a Mean (incl. t-distrib) |

. | 2013-11-06 | Wed | 10 | Hypotheses and Test Procedures; Errors in Hypothesis Testing; Proportion |

. | 2013-11-08 | Mon | 10 | Hypothesis Tests for Population Mean; Power and Probability of Type II error |

. | 2013-11-13 | Wed | 11 | 2-sample t-test for means (indep); 2-sample t-test for means (paired) |

. | 2013-11-15 | Mon | 11 | 2-sample z-test for proportions; multiple testing(?) |

. | 2013-11-20 | Wed | 12 | Categorical Data: Goodness-of-Fit |

. | 2013-11-22 | Mon | 12 | Independence/Homogeneity |

. | 2013-11-27 | Wed | break | Thanksgiving Break |

. | 2013-11-29 | Mon | 13 | Linear Regression and Correlation: Inferential Methods |

. | 2013-12-04 | Wed | calc | Joint PMFs; calculus-based methods; PROPOSAL DUE |

. | 2013-12-06 | Mon | review | review day |

. | 2013-12-11 | Wed | Final | final exam during last day of class |

. | 2013-12-16 | Mon | No Monday Class (other classes having finals) | |

. | 2013-12-17 | Tue | presentations during final exam slot, 11am | |

. | 2013-12-18 | Wed | presentations during final exam slot, 11am |

Some variations in this outline are to be expected.

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 whiteboard, 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. All homework should be typed and submitted via the EMU-Online Dropbox. The policy is: if it isn't in the Dropbox, it doesn't exist.

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:

- 10 pct: proposal
- 80 pct: work and written report
- 10 pct: presentation file (PowerPoint, usually)

On average, students should spend a total of about 30 minutes in office hours discussing the project. Plan for this in advance!

No scores will be dropped, unless a valid medical excuse with evidence is given. In the unfortunate event of a medical 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:- 50 percent for all the homework, possible quizzes, and the project together,
- 20 percent for the midterm exam
- 30 percent for the final exam.

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 Athough if absolutely necessary, a curve might be applied.

- * work in groups * start the first day assignment is given * don't take too many credits w/ this class * ask a lot of questions * utilize Dr. Ross
- Do go to his office hours more than you normally would; if you have a question ask don't wait.
- See Prof. Ross in office hours and don't be afraid to email him. He is usually very helpful and approachable.
- Plan on visiting Prof. Ross during office hours in order to do well in the class. You will learn a lot in the end, but be ready to work.
- attend the office hours Prof Ross is really good at explaining & helping out with the homework
- WORK TOGETHER!
- Take notes during the computer lab days and send yourself the excel sheets.
- Go to class. The computer lab days help even if you know excel well.
- Go to class. Go to office hours and pick project that you're energized about and interested in even if they're harder. It will make this math class the best one you've ever taken.
- Don't drop the class! It sounds impossible in the beginning, but stick with it.
- Don't procrastinate.
- Start projects ASAP.
- Ask questions!!! The professor will guide you along the way like Yoda.
- Talking to anyone about your projects or the homework, be it Prof. Ross or other students, is a really, really good idea.
- Never be afraid to ask for help.
- If project falls through, have backups.

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.

Current University policy recognizes the rights of students to observe religious holidays without penalty to the student. Students will provide advance notice to the instructor in order to make up work, including examinations, they miss as a result of their absence from class due to observance of religious holidays. If satisfactory arrangements cannot be made with the instructor, the student may appeal to the school director or head(s) of department(s) in which the course(s) is / are offered.

Academic dishonesty, including all forms of cheating, falsification, and/or plagiarism, will not be tolerated in this course. Penalties for an act of academic dishonesty may range from receiving a failing grade for a particular assignment to receiving a failing grade for the entire course. In addition, you may be referred to the Office of Student Conduct and Community Standards for discipline that can result in either a suspension or permanent dismissal. The Student Conduct Code contains detailed definitions of what constitutes academic dishonesty but if you are not sure about whether something you are doing would be considered academic dishonesty, consult with the course instructor. You may access the Code online at: www.emich.edu/studentconduct/

Students are expected to abide by the Student Conduct Code and assist in creating an environment that is conducive to learning and protects the rights of all members of the University Community. Incivility and disruptive behavior will not be tolerated and may result in a request to leave class and referral to the Office of Student Conduct and Community Standards (SJS) for discipline. Examples of inappropriate classroom conduct include repeatedly arriving late to class, using a mobile/cellular phone while in the class session, or talking while others are speaking. You may access the Code online at www.emich.edu/studentconduct/

When we aren't in a computer lab, if ever, those who use laptops during class should sit in the back row if possible, to avoid distracting others with what is on their screens.

If you wish to be accommodated for your disability, EMU Board of Regents Policy 8.3 requires that you first register with the Disability Resource Center (DRC) in 240K EMU Student Center. You may contact DRC by telephone (734.487.2470). Students with disabilities are encouraged to register with the DRC promptly as you will only be accommodated from the date you register with them forward. No retroactive accommodations are possible.

The Student Exchange Visitor Information System (SEVIS) requires F and J students to report the following to the Office of International Students 244 EMU Student Center within ten (10) days of the event:

- Changes in your name, local address, major field of study, or source of funding;
- Changes in your degree-completion date;
- Changes in your degree-level (ex Bachelors to Masters)
- Intent to transfer to another school.

- Dropping ALL courses as well as carrying or dropping BELOW minimum credit hours;
- Employment on or off-campus;
- Registering for more than one ONLINE course per term (F visa only)
- Endorsing I-20 or DS-2019 for re-entry into the USA.