Syllabus Stat 202 Fall 2017
Basic Statistics (Stat 202) Fall 2017 Sections 002 & 005 & 007
Instructor: Sean Carver, Ph.D., Professorial Lecturer, American University.
- office location (changed since August 1, 2017): Don Myers Building (East Campus), Room 208F
- email: firstname.lastname@example.org
- office phone: 202-885-6629
Course Description (from department website): Data presentation, display, and summary, averages, dispersion, simple linear regression, and correlation, probability, sampling distributions, confidence intervals, and tests of significance. Use of statistical software both to analyze real data and to demonstrate and explore concepts. Four credit hours.
A Word of Warning: The Math/Stat Department at AU teaches STAT 202 to prepare students to use statistics in advanced courses required for many majors. Thus the STAT 202 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 202 is an easy class based on your effort and performance in the first weeks of the class. The last weeks of the class are the hardest.
Prerequisite: MATH-15x or higher, or permission of department. No prior knowledge of statistics is assumed.
Required Text: Intro to Practice of Statistics, Edition: 7th, 8th, or 9th. Available new, used, or through LaunchPad, online version, (12 month subscription for about $100, free for the first several weeks): http://www.macmillanhighered.com/Catalog/Product.aspx?isbn=1464133409 .
Statistical Software: R, R-Studio, and StatCrunch (all free to AU students). R is unquestionably the most powerful statistical software package available. R-Studio is a program that provides a graphical interface to R. StatCrunch, on the other hand, provides an alternative to R, which is very easy to learn, and is a great pedagogical tool, however its usefulness outside the classroom is limited. 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. Free access to StatCrunch will end when you leave AU.
Please Bring A 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. You may borrow a computer from the library.
Learning Outcomes: These learning objectives may be tweaked and edited throughout the semester.
By the end of the course, the student should be able to:
Concerning R and R-Studio
- Use R-Studio console command line and editor.
- Understand R variables, functions, and function arguments.
- Install R packages.
- Access and understand R help files.
- Use R for basic statistics.
Concerning Basic Statistics
- Use and understand common statistical terminology.
- Understand data collection methods including designed experiments and sampling methods.
- Know when to use stem plots, histograms, pie charts, bar charts, and box plots to describe a given distribution.
- Calculate and interpret the measures of center and spread.
- Understand the concepts of correlation and linear regression.
- Understand the concepts of randomness and probability.
- Understand and interpret probability distributions such as the normal, student's t- and chi-square distributions.
- State the central limit theorem and understand the concept of a sampling distribution.
- Understand the paradigms of tests of significance, including what a p-value is.
- Perform tests of significance involving means and proportions, both one and two samples.
- Calculate confidence intervals for means and proportions.
Office Hours: Students are strongly encouraged to come to office hours if they need or want help. Lately, I have been holding office hours on the weekends as well as during the week. I encourage students to come on the weekend, if they want help with R, statistical software, or projects, but you can come on the weekend for any reason. That said, I am in the middle of moving my home to a new apartment, because this is consuming a lot of my time, I have decided to not yet commit to weekend office hours, until I am more settled. Instead:
- You can make an appointment with me in advance (you are encouraged to do this).
- You can stop my office, without an appointment, Tuesdays, Wednesdays, and Fridays between 11:30 and 12:30, and between 2:30-3:30, but if I am not expecting you, I may step away from my desk.
- Weekend office hours coming soon...
SI Leader: Colleen Reynolds will be your Supplemental Instruction (SI) leader this fall. Colleen is a senior majoring in public health, who took my class last fall. She will be leading one-hour group study-tutoring sessions twice per week for the course. While these session are not mandatory, they are an opportunity for students looking to improve their performance in the class to ask questions, discuss concepts, practice problems, and receive additional help. Colleen’s goal this semester is to help you master the material, enjoy the class, and understand how statistics can be a useful tool for students in any major. If you have questions about the SI program, you can email Colleen at: email@example.com. Times and locations will be announced by the end of the second week of class. More information about the program can be found at: http://www.american.edu/ocl/asac/Supplemental-Instruction-Homepage.cfm
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: Don Myers Building, Room 103, walk-ins welcome. See http://www.american.edu/cas/mathstat/tutoring.cfm
Lab Hours during Fall Semester:
- Monday - Thursday: 11:00 AM - 8:00 PM
- Friday: 11:00 AM - 3:00 PM
- Sunday: 3:00 PM - 8:00 PM
- Saturday: Closed
- Contact: Dr. Behzad Jalali
- Phone: 202-885-3154
- Alt Phone: 202-885-3120
- E-mail: firstname.lastname@example.org
Class times and locations:
- Section 002: Tuesdays, Wednesdays(*), and Fridays: 12:55PM-02:10PM in KRWN 302.
- Section 005: Tuesdays, Wednesdays(*), and Fridays: 09:45AM-11:00AM in KRWN 303.
- Section 007: Tuesdays, Wednesdays(?), and Fridays: 04:05PM-05:20PM in KRWN 302.
- (*/?) Wednesday classes end 15 minutes early, but this wasn't noted for in the Schedule of Courses for Section 007, will check, but I believe this was an error.
- Tuesday, August 29, First Day of Class.
- Friday, September 8, Optional Project Brainstorm.
- Friday, September 22, Midterm.
- Friday, September 29, Optional Project Proposal Due.
- Friday, October 13, Fall Break, no class
- Friday, October 27, Optional Project Update Due.
- November 21-26: Thanksgiving Break, no class all week.
- Friday, December 8: Last Day of Class.
- Saturday, December 9: Optional Projects Due (Hard copy in my mail box.)
- Friday December 15: Final Exams, see below for times, locations to be decided.
- For the class that meets TWF, 09:45AM-11:00AM: Your exam is 12/15/2017, 08:10AM-10:40AM.
- For the class that meets TWF, 12:55PM-02:10PM: Your exam is 12/15/2017, 11:20AM-01:50PM.
- For the class that meets TWF, 04:05PM-05:20PM: Your exam is 12/15/2017, 02:30PM-05:00PM.
Optional Extra-credit Projects: 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. You are encouraged to publish your work on my web server: http://stat370.com/. It is easiest to do this in R-Markdown and I will show you how. Unfortunately my server will be down until further notice (perhaps two weeks), as I am moving to a new apartment. You may also turn in a paper, a PowerPoint presentation, a statistical dashboard (Google this, if you do not know what this is), a YouTube video, etc. I do not accept submissions by email. You must turn in a hard copy (hard copy of a link, if it is also posted on my web server). 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. Exceptional and brief PowerPoint presentations will be invited to be presented in class, if there is time, and if it furthers the course objectives. Presenting your work to the class is optional.
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 (E.g. R-Markdown) 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.
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 recently (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.
Data discussion and initial project brainstorm, Thursday, July 6:
- You can get extra credit (3 quiz points) for doing the data discussion preparation whether or not you choose to do a project. You must be present in class on Thursday, July 6, 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: 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, Thursday, July 13:
- Turn in one or a few paragraphs describing what you would like to do. You are encouraged to discuss your project idea with me, both before and after you submit your proposal.
The project update, Thursday, July 27:
- Turn in several paragraphs describing what you have done so far and what problems you have run into. Most important: include a plan for completing your project.
Final projects due August 10 (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:
|Attendance and Participation||10%|
|Extra Credit Data Discussion Preparation Write-up||+ 3 Quiz Points|
|Extra Credit Project||+ 0-3%|
Quizzes and Exams: Quizzes are worth 40% of your grade. The Midterm is worth 10%. The Final is worth 40%. For both the quizzes and the exams, you will have access to a computer. Specifically, you will permitted to use R, R-studio, StatCrunch and a calculator app. You will not be able to do Google searches, access this website, or use your computer in any other way, unless specifically cleared by the instructor. All problems that require computer use on the final will be problems that can be solved with StatCrunch, however quizzes may contain problems that require R and R-studio. There may not be a quiz every day, in fact usually it will be once a week. Nevertheless, be prepared to take a quiz during every class (except the first two). Quizzes will take place toward the beginning of the class, so show up on time. Note that your lowest 5 quiz scores will be dropped. This large number of dropped quizzes is to accommodate students who occasionally need to miss class or arrive late. There will be absolutely no make-up quizzes, as the solutions to the quizzes will be discussed in class immediately after the quiz. Absences on exam days must be excused through the Dean of Students, who needs to send a letter to me indicating that they excuse your absence. If excused through the Dean of Students, you do not need to disclose the reason to me.
Homework Problems: I will pass out homework problems, but I will not collect them. We will work on the problems in class, and I will go over the answers, as well. You are encouraged to complete homework problems that you do not finish in class, on your own. You are also encouraged to use these problems to review.
Attendance and Participation: You are expected to attend every class. However, there can be compelling reasons why you need to miss class, once in a while. Please email me if you are not going to attend. If we have a quiz that day, it will need to be one of the 5 I drop. I may not take attendance every class, but I am usually aware if a student misses frequently, and if that is you, you lose all credit in this category (10%, but you will get a warning, first). Please drop the class if you cannot attend regularly. Though my policy on attendance is pretty liberal, you are warned not to abuse it. Coming to class is very important for learning the material. Every day builds upon the material previously, and missing class puts you at a disadvantage, even if it is for a good reason.
Class Etiquette: Please give the class your full attention and refrain from talking, texting, surfing the web, and similar distractions. If it is clear to other students that you are not paying attention, it will be harder for them to pay attention to me. This statement is true in general, but it is especially true if you are talking. Also, it can also be harder for me to give good lectures, when it is clear that not everyone is paying attention. Like you, your classmates are paying a lot of money to be here. Have some respect for your fellow students! Otherwise you are negatively impacting their educational experience, which isn't fair to them. If you need to attend to something urgently, it is OK to excuse yourself from the classroom. Please be warned that if people are not following this request, I may reread this statement to the class.
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. I find it easier to give good lectures when students are asking questions, and engaging with the material.
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 quizzes or 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.
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 (email@example.com)
- AU's Coordinator for Victim Advocacy Sara Yzaguirre (firstname.lastname@example.org)
- 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 email@example.com 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.)