Difference between revisions of "Syllabus: Stat 203 Fall 2016"

Latest revision as of 20:48, 7 September 2016

Basic Statistics with Calculus (Stat 203) Fall 2016 Section 002

Materials: [Lectures Notes 203 (Fall 2016)][Old Lectures Notes (Previous Semesters)][Homework][Data][Links and Other Materials][Practice Problems]

Instructor: Sean Carver, Ph.D., Professorial Lecturer, American University.

Contact:

• office location: 107 Gray Hall
• email: carver@american.edu
• office phone: 202-885-6629

Course Description (from department website): A calculus-based introduction to basic statistics including data presentation, display and summary, correlation, development of least squares regression models, probability, independence, probability density functions, moments, use of moment generating functions, sampling distributions, confidence intervals, and tests of significance. Concepts are explored through simulation and the use of the calculus tools of finding maxima and minima of a function and the area under a curve. Note: students may receive credit for only one of STAT-202, STAT-203, or STAT-204.

A Word of Warning: The Math/Stat Department at AU teaches STAT 203 to prepare students to use statistics in advanced courses required for many majors. Thus the STAT 203 instructor does not always have the luxury of setting the most comfortable and easy pace through the course material. The pace will be determined by what we need to cover for your future classes. There is a lot of material in the curriculum, so be prepared to work hard and spend a lot of time studying outside of class.

Another Word of Warning: The material at the beginning of the class is much easier than the material at the end. Do not assume that Stat 203 is an easy class based on your effort and performance on the first exam, or even on your effort and performance on the first two exams. The second exam is harder than the first and the last exam is the hardest.

Prerequisite: MATH-221 or one semester of calculus.

Text: Intro to Practice of Statistics, Edition: 8th. (About $200, new from Amazon.) Online version of textbook (12 month subscription for about $100): http://www.macmillanhighered.com/Catalog/Product.aspx?isbn=1464133409 . Every night, there will be reading assignments from the text involving the material we just covered. We will discuss this reading next class, when I review.

Software: StatCrunch (web-based software), accessed from a browser with this link: http://statcrunch.american.edu/. From this link, StatCrunch is free with AU credentials. You can also access StatCrunch from StatCrunch.Com but you will need to pay for access through this site.

Bring Your Laptops To Class! I will be demonstrating software in class with the idea that you follow along with your own computer. Additionally, I will be giving problems to solve in class that require a computer. If you do not have a laptop of your own, you may be able to borrow one from the library.

Learning Outcomes: These learning objectives may be tweaked and edited throughout the semester. (Credit: Prof. Malloy.)

STAT 203 is an introduction to statistics that emphasizes working with data and using statistical reasoning. Topics covered include: classification of data, averages, variability, probability, frequency distributions, confidence intervals, tests of significance, least squares regression, and correlation. A computer package is used to demonstrate statistical techniques and concepts.

Major focus for this course is on the ideas behind, and the methods for, drawing conclusions about a population from a sample. At the end of this course you will be expected to (1) identify the major concepts related to statistical reasoning and to statistical inferences for drawing such conclusions, (2) recognize how these concepts are used in experiments and observational studies across many disciplines, and (3) implement the methods yourself in statistical analyses. Work will be a balance between understanding the concepts underlying a method, implementation of the method, and interpretation of the results. The mathematical foundation of the methods using Calculus will be emphasized.

This course is divided into four related areas of study:

• Data collection – the theory and practice of study design.
• Data summary and exploration – which illustrates to us how the data actually behave.
• Probability and sampling theory – from which we determine how we expect the data to behave.
• Data analysis – which allows us to reconcile our expectations with the actual data behavior so that we can make statistical inferences and drawing conclusions.

Office Hours: Students are strongly encouraged to come to office hours if they need or want help.

My office is Gray Hall, Room 107. Office hours are TENTATIVELY scheduled as follows: (may be adjusted throughout the semester)

• Monday, Wednesday, Thursday: 2:30 PM TO 4:30 PM.

NOTE: If you would like to come to office hours on a regular or irregular basis and you have a compelling reason why you cannot make it during the hours listed above, please send me an email. I cannot guarantee that I will be able to find a time that works (this semester will be a very busy one for me), but I will try.

Tutoring through AU's Academic Support and Access Center. By appointment. See http://www.american.edu/ocl/asac/Tutor-Services.cfm

Tutoring through MATH/STAT tutoring center: Gray Hall, Room 110, walk-ins welcome

• Monday - Thursday: 11:00 AM - 8:00 PM
• Friday: 11:00 AM - 3:00 PM
• Sunday: 3:00 PM - 8:00 PM
• Saturday: Closed
• The Tutoring Lab will open on September 6th
• Contact: Dr. Behzad Jalali
• Phone: 202-885-3154
• Alt Phone: 202-885-3120
• E-mail: bjalali@american.edu,

Class times and locations:

• Section 2: Monday, Wednesday, Thursday: 12:55 PM TO 2:10 PM, ANDERSON B-12 (Wednesday's class ends 15 minutes early).

Important Dates:

• August 29 (Monday): First day of class.
• September 5 (Monday): Labor Day, no class.
• September 8 (Thursday): Getting Data Discussion and Extra Credit Preparation due.
• September 15 (Thursday): Extra Credit Project Proposal due. Also, last day to indicate your intention to do election day data collection, and choose your partner.
• Tentative: September 22 (Thursday): Exam 1.
• October 17 (Monday): Extra Credit Project Updates due.
• Tentative: November 3 (Thursday): Exam 2.
• November 8 (Tuesday): Election Day - Extra Credit Data Collection happens on that day.
• November 10 (Thursday): Extra Credit Data Collection Write-Up due
• November 22-27 (Tuesday-Sunday): Thanksgiving Break, no class.
• December 8 (Thursday): Last day of class, and Extra Credit Projects due.
• December 15 (Thursday): 11:20-1:50. Final exam.

• See also AU's academic calendar: http://www.american.edu/provost/registrar/upload/Academic-Calendar-2016-2017-Inc-WCL-20160720.pdf

Optional Extra-credit: I give you the opportunity to complete an optional extra-credit project. These projects can be a lot of work, but they can also be, for less extra credit, much less work. Topics will be different for each person. Your project must relate to statistics. Your project must involve effort that has an educational benefit to you. There must be a component of the project that communicates your results to me, as either a paper, a PowerPoint presentation, a statistical dashboard (Google this, if you do not know what this is), a YouTube video, etc. If doing a YouTube video, email me the link and include it in the written part you turn in. (Obviously, you won't print out a video, but, as explained below, there is more to turn in, and a printed link should be included.) For all other media, you must give me a hard copy. PowerPoint presentations should be turned in as a printout of the slides -- also, if there is time, you can present the PowerPoint to me during office hours, but it must be before the deadline. For PowerPoint printouts, black and white, reduced sized, images are fine, as long as they are readable.

The suggested project involves obtaining data from the web, exploring the data, asking and answering questions with statistics, then communicating the results in a compelling way. In addition to working with data, there can also be independent study, library research, interviews of statisticians, etc. Part of your project could be learning a software tool useful for statistics or data science. If you want to collect your own data, (I actually discourage this), you MUST do it in a scientifically acceptable way. This semester, there is a separate election day data collection project that is worth more points. These projects can be combined (collection and analysis) for credit on both.

If these projects sound like a lot of work, they can be, but remember that they are optional and extra credit. You will get some credit for anything you do along these lines, and anything you do will help you.

If you are thinking of doing a project, please work with me to decide on a project topic. We will also brainstorm ideas in class. Pick a topic and a project that excites you. Your project should relate to your passions, goals, dreams and/or interests. My idea is that you will really want to do this project which is why I am giving you a lot of freedom to design it.

Suggested topics (actually, whatever interests you): sports (of various kinds, there are lots of free good data on baseball), entertainment, movies (again good data), law, criminology, government, city planning, architecture, weather, climate, geology, seismology, medicine, epidemiology, health, fitness, biology, evolution, extinction, ecology, math, computer science, statistics, data science, anthropology, ethnic studies, gender studies, history, sociology, culture, tourism, archeology, art, literature, writing, journalism, census, linguistics, finance, economics, business, astronomy, physics, chemistry, library sciences, theology, anything else you can think of.

Curated data sets exist for many of these topics, although some cost money. For curated data sets, free or otherwise, you just download them, although sometimes you have to do more work to get the data into a usable format.

A more advanced technique is to use a "web scraper" which masquerades as a browser and pulls data directly from the web. One student was successful at doing this last Spring (she used a website dedicated to this effort). Some websites have their own Application Programming Interfaces (API) which facilitate this process (examples: twitter, facebook, linked in). These more advanced techniques may be difficult, and often involve computer programming. I am a computer programmer, but I do not have a lot of experience with web scraping. That said, I have a lot of books on the subject and would love to learn how. If you are interested, let's try it together during office hours.

Last Spring, I gave some students extensive help on their projects. Help does not count against you, even extensive help. Many other students did not ask for help, and that is OK, too. Of course, some students chose to not even do a project, which was also fine. (If you don't do a project, you won't get any extra credit, but it won't count against you, either). Anything you choose is fine with me, but if you want help, ask early and come to office hours in the beginning, and all throughout the semester. Things can get busy toward the end, both for you and for me. Starting early will also give you more time, and you will need time to do these projects well. You can also get help from other sources (family, friends, other professors, etc), but you must disclose the help you receive in writing in an "acknowledgements" section, when you turn it in. That said, I encourage you to get help, if you need or want it, as long as you do not take credit for others' work. Along these same lines, cite your sources. You must also cite the source(s) of your data.

There are several planned milestones with due dates for completing the project:

• September 8 (Thursday): Getting Data Discussion and Extra Credit Preparation due.
• September 15 (Thursday): Extra Credit Project Proposal due. Indicate participation in election day data collection and choose a partner.
• October 17 (Monday): Extra Credit Project Updates due.
• November 8 (Tuesday): Election Day - Extra Credit Data Collection happens on that day.
• November 10 (Thursday): Extra Credit Election Data Collection Data and Write-Up due
• December 8 (Thursday): (Last day of class, and) Extra Credit Projects due.

Data discussion, September 8:

You can get extra credit (1 homework) for doing the data discussion preparation whether or not you choose to do a project. Due Thursday, September 8. You must be present in class on Thursday, September 8 to get the points, and you must both participate in the discussion in class and turn in (that same day) a short written piece (one or a few paragraphs) describing your experience with the assignment and answering the questions below. To complete the assignment, pick a topic, suggestions are listed above. See what data you can find on the web concerning this topic. Use Google, and start with the key words "data" and your topic. Are the data you find free or do they cost money? Can you download the data set or do you need a computer program (or hand copy) to pull them off the web? If you can download the data, can you load it into StatCrunch or do the data require "munging" to be used by StatCrunch? Then answer the following questions (you should know how by September 8): What are the cases, and what are variables? (If there are many variables, what are some of the ones that are of interest to you?) Spend at least 45 minutes on this assignment. If you finish with your first topic in less than 45 minutes, try another topic.

The project proposal, September 15:

Turn in one or a few paragraphs describing what you would like to do. If you intend to participate in the election day data collection (whether or not you are doing a project) please indicate your intention on a separate sheet of paper, submitted together with your name and the name of your chosen partner (each pair turns in one sheet of paper). If you haven't found a partner by class time on September 15, don't worry. Single participants will pair up during the September 15 class.

The project update: October 17 (Monday).

Turn in several paragraphs describing what you have done so far and what problems you have run into.

Election Day Data collection: November 8 (Tuesday).

This is a project run by Mary Gray, another professor in Statistics. Participation in the data collection is separate from the project. You can get credit for one project, or the other project, or both. Your main project can involve the data being collected on election day (yours and everyone else's) but it doesn't have to. See Professor Gray's description of the whole project here here.

Data due: November 10 (Thursday).

Turn in the data you collected and a write up of your experience (one or a few paragraphs) to me (Carver) on November 10 (Thursday) or November 9 (Wednesday) and I'll pass the data along to Professor Gray.

Final projects due December 8 (Thursday): (Last day of class).

There are various allowed formats for the final project write up (paper, PowerPoint Presentation, Data Dashboard, YouTube video, etc, described above). Whatever format you choose, your final projects must have an addendum titled "behind the scenes" which describes how you did the project and where you got your data, and must also include an acknowledgements section. Additionally, optional sections may include "dead-ends" and "dreams for the future" for which you will get credit for things that did not work, or good ideas you had which you did not have time to implement. Creativity will be rewarded!

Grades will be awarded as percentage points added to your final score. Typically, this will be up to 3 percentage points added to your final grade. A perfect "3" will generally be a project which is a good start of something that looks promising for publication. Fractional scores (e.g. 2.5) may also be awarded. Some credit will be given for partially completed projects, but you must complete the milestones by the deadlines.

Tentative grading scheme:

Class Etiquette: Please give the class your full attention and refrain from talking during lectures, texting, surfing the web, and similar distractions. If you need to attend to something urgently, it is OK to excuse yourself from the classroom.

Please participate in class by asking questions when you do not understand something. Invariably other students benefit from these questions. Please engage in discussions, and please engage with the class, generally.

Academic Integrity: Cheating is not acceptable and will not be tolerated. Consider this: in subtle ways, cheating to get a better grade on an exam can result in lowering the grades of some of your classmates. Certainly this is true when a specific curve is used to assign grades. Even when I don't use curves explicitly, they can be implicit in decisions about writing and grading exams. As required by the policy of American University, I will report all suspected cases of cheating to the Dean's office who will proceed to investigate and adjudicate the issues. Cheating is giving or receiving unauthorized assistance on exams, from other students or other people, from notes, from books, or from the web. When inappropriate copying between students is caught, both parties may be culpable.

Homework, Attendance and Participation Policy: Homework is worth 10% of your grade, with each assignment weighted equally (10 points maximum). The due date for homework is technically the end of class, one week after it is assigned, however you should make every effort to complete each assignment as soon as possible. That said, you can turn in homework anytime, up to Wednesday, December 7. Homework turned in after the technical due date will receive a maximum of only half credit (5 points). I plan to post deadlines on this website.

I like to give the solutions to homework problems at the same time I assign the problems. Conscientious students, who wrestle with problems before looking at the answers, benefit from having instant feedback about their solutions, right, wrong, or incomplete. Less conscientious students who use the answers to easily complete the assignments often do poorly on exams. The responsibility for your education rests in your own hands. Don't be one of the outliers who use shortcuts to avoid preparing for the exams. Concerning homework, you are encouraged to work with your classmates, if you find that helpful. In fact, you are encouraged to do whatever you find most helpful with the homework, but by turning in a solution to a problem, you pledge that you understand the solution, or that you talked to me in office hours or during or after class and made a good faith effort to understand how to do the problem. If it looks like you got the full benefit from the assignment, and if you turn it in by the due date, I will award you a perfect 10 points. I may mark you down if it seems that you have copied the answers without including any of the required calculations. You must include your work.

Additionally, 15% of your grade is for class attendance and participation. I understand that there are times when you cannot make it to class for compelling reasons. To accommodate the unavoidable, I will forgive a fixed number of absences for everyone when I compute the final grades. If you need to miss more than several classes, please see the Dean of Students. I will only erase absences from my grade book with a request through the Dean of Students. That said, I do appreciate an email when you can't make it to class. Absences on exam days must be excused through the Dean of Students.

I plan to post grades to Blackboard, promptly.

Public Service Announcement: A representative of AU's Students Against Sexual Violence (SASV) approached me and asked me to include on my syllabi a list of resources available for survivors of sexual assault and their friends. While sexual violence is by no means the only challenge faced by students, I agree that this issue merits particular attention, so I am honoring her request by attaching the list she gave me:

Sexual Assault Resources

• It’s never the survivor’s fault. There are many people you can talk to if you or someone you care about has been sexually assaulted:

• AU's Office of Advocacy Services for Interpersonal and Sexual Violence (OASIS): http://www.american.edu/ocl/wellness/sexual-assault-resources.cfm

• AU's Sexual Assault Prevention Coordinator Daniel Rappaport (rappapor@american.edu)

• AU's Coordinator for Victim Advocacy Sara Yzaguirre (sarayza@american.edu)

• Rape, Abuse & Incest National Network hotline: 1-800-656-HOPE and https://ohl.rainn.org/online/

• DC SANE Program (Sexual Assault Nurse Examiner) 1-800-641-4028

• The only hospital in DC area that gives Physical Evidence Recover Kits (rape kits) is Medstar Washington Hospital

• DC Rape Crisis Center: 202-333-7273

• Students found responsible for sexual misconduct can be sanctioned with penalties that include suspension or expulsion from American University, and they may be subject to criminal charges

• If you want to submit a formal complaint against someone who has sexually assaulted you, harassed you, or discriminated against you based on your gender identity or sexual orientation, you can do so online at http://www.american.edu/ocl/dos/, or contact the Dean of Students at dos@american.edu or 202-885-3300. These are Title IX violations, and universities are legally required to prohibit these actions.

• Resources on campus that are required to keep what you tell them confidential are Daniel Rappaport, Sara Yzaguirre, ordained chaplains in Kay, and counselors at the counseling center. (OASIS may also belong here but it didn't exist when this list was created.)