Difference between revisions of "Syllabus: Stat 202 Spring 2017"

Latest revision as of 02:13, 17 January 2017

Basic Statistics (Stat 202) Spring 2017 Section 001

Materials: [Course Materials Spring 2017][Old Lectures Notes (Previous Semesters)][Active Learning Exercises with Solutions][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): 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 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-15x or higher, or permission of department. No prior knowledge of statistics is assumed.

Text: Intro to Practice of Statistics, Edition: 8th. Available through LaunchPad, online version, required for homework (12 month subscription for about $100): http://www.macmillanhighered.com/Catalog/Product.aspx?isbn=1464133409 .

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.

By the end of the course, the student should be able to:

• Use and understand common statistical terminology.
• Understand data collection methods including designed experiments and sampling methods.
• Know when to use stemplot, 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.
• Calculate confidence intervals for means and proportions--one sample.
• Use sampling techniques to test hypotheses for means and proportions--one and two samples, contingency table, and goodness-of-fit.

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)

• Tuesday, Wednesday, Friday: 4:00 PM TO 6:00 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

Hours for Fall 2016 (Spring 2017 hours not yet posted)

• 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 is not always open during the first week of the semester. Call ahead.
• Contact: Dr. Behzad Jalali
• Phone: 202-885-3154
• Alt Phone: 202-885-3120
• E-mail: bjalali@american.edu,

Class times and locations:

• Section 3: Tuesday, Wednesday, Friday: 2:30 AM TO 3:45 PM, WARD 302 (Wednesday's class ends 15 minutes early).

Important Dates:

• January 17 (Tuesday): First day of class.
• January 20 (Friday): Inaugaration Day, no class.
• January 24 (Tuesday): Initial Project Brainstorm (come with ideas).
• February 10 (Friday): Midterm Exam 1. Location to be decided.
• February 14 (Tuesday): Extra Credit Project Proposals due.
• March 12 - 19: Spring Break, no class.
• March 21 (Tuesday): Extra Credit Project Updates due.
• March 31 (Friday): Midterm Exam 2. Location to be decided.
• April 28 (Friday): Last day of classes and extra credit final projects due.
• May 9 (Tuesday), 2:30 PM - 5:00 PM: Final Exam. Location to be decided.
• May 12 (Friday): Grades due to registrar

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, 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.

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.

Data discussion and initial project brainstorm, January 24:

You can get extra credit (1 homework) for doing the data discussion preparation whether or not you choose to do a project. You must be present in class on Tuesday, January 24 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 January 24): 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, February 14:

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: March 21.

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

Final projects due April 28 (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, 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 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.

Attendance: You are expected to attend class unless there is a compelling reason why you cannot make it. Attendance is worth 5% of your grade. Beyond the 5%, I believe that excellent attendance will be necessary to meet the objectives of this class. However, I understand that there are times when you cannot make it to class for compelling reasons. To accommodate the unavoidable, I will forgive occasional absences for everyone when I compute the final grades. If you need to miss more than a few classes, please see the Dean of Students. Exam day absences must be excused through the Dean of Students. On other days, please send an email to me when you can't make it to class, explaining why. If your attendance is not acceptable, you will receive an early warning from me through the registrar. This is how you will know you are in danger of losing the credit for attendance. If your attendance continues to be poor, you might miss all 5% on attendance (i.e. get a zero in this category).

Homework: Homework is worth 20% of your grade. Homework will be administered and auto-graded through the publisher's website LaunchPad. Additionally, there will be optional practice problems with solutions handed out during class.

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.)