Course Syllabus

Statistics: Measurement in Economics

Econ 310 (4 Credits), Summer 2018

University of Wisconsin-Madison

Instructor: Christopher McKelvey

E-mail: cmckelvey@wisc.edu

 

Course Webpage

Begin the course on Monday, May 28 by going to the website: http://canvas.wisc.edu/

Course Overview

This six-week online course provides an introduction to statistics.  We will tackle three main topics.  We begin with an overview of descriptive statistics and statistical terminology.  Next we turn to probability, a branch of mathematics which provides us with the methods necessary to reason about uncertain environments.  Finally, we turn to the bread and butter of statistics: estimation and inference.  Particular attention will be paid to the application of these tools to the analysis of economic data.

Prerequisites

Prerequisites for this class include (a) an introductory economics course and (b) Math 211 or Math 221.

Class Meetings and Office Hours

This is an online course.  There is no need for you to be physically present in Madison at any point during the six week term.  However, you must have access to a reliable internet connection for the duration of the course (May 28 - July 6).

I will be holding online office hours throughout the semester.  A schedule of office hours along with instructions on how to attend will be available via the course website.

Textbook and Required Materials

Keller, Gerald (2018).  Statistics for Management and Economics, Bundled with Aplia. Cengage Learning, Eleventh Edition.

We’ll be using Aplia extensively for this class, so it is essential that you buy a “book plus Aplia” bundle, not simply the book alone.  There are two options for obtaining an Aplia bundle:

• Option 1 – If you are happy with electronic-only access to the textbook, when you log into your Aplia account you will be given an opportunity to buy a semester of access for roughly $100.
• Option 2 – If you prefer a physical textbook, University Bookstore sells an Aplia bundle that includes a loose-leaf edition of the text for roughly $170.

This course requires frequent use of a computer (Mac or Windows) with a reliable internet connection.  While completing the problem sets, quizzes, and final exam, you will need a calculator with the following functions: x^y, x!, and e^x.

Evaluation

Your overall grade for the course will be based on four components:

• Aplia Problem Sets:  Each Monday through Thursday, Aplia problem sets will be due daily by 11pm Central Time (UTC−5:00).  The Aplia problem sets are worth 30% of your overall grade for the course, so completing them will be critical to your success.  Late problem sets will not be accepted for any reason, but your lowest three Aplia problem set scores will be automatically dropped.  To give everyone a bit of scheduling flexibility, it will be possible to work several days ahead, if you so desire. 
  
• Stata Logs: At several points in the term, I will ask you to perform computer work in Stata and upload the resulting log file.  To give everyone a bit of scheduling flexibility, it will be possible to submit your log file several days in advance, if you so desire.  Log files will be graded and are worth 10% of your overall grade for the course.
  
• Weekly Quizzes: Each Friday for the first 5 weeks, there will be an open-book, open-note quiz covering that week's material.  These quizzes will be time constrained and must be completed at some point in the 24 hour period corresponding to Friday in the Central Time Zone (UTC−5:00).  Together the quizzes will make up 40% of your overall grade for the course. Quizzes will not be rescheduled for any reason.  On a case by case basis, in the event of truly unavoidable circumstances (submit a written statement in advance), I may elect to shift the weight of a missed quiz to a subsequent quiz.  A cold or flu does not constitute an unavoidable circumstance –  a medical emergency must be severe enough to make completion of the quiz impossible and must be fully documented.
  
• Final Exam: On the final Friday of the term (July 6), there will be an open-book, open-note cumulative final exam.  As with the quizzes, the final exam will be time constrained and must be completed at some point in the 24 hour period corresponding to Friday in the Central Time Zone (UTC−5:00).  The final exam is worth 20% of your overall grade for the course.
  

On all quizzes and exams, you must work alone.  In other words, you are not permitted to receive outside help of any kind.

Your overall grade for this class will be curved. This curve can help your grade, but cannot hurt it.  I achieve this by computing your grade using two different methods. First, I assign grades according to a percentage scale, where A = [92,100], AB = [88,92), B = [82,88), BC = [78,82), C = [70,78), D = [60,70), F = [0,60). (In other words, if you receive a grade in the class of 92% or better, then you’ll receive an A.) Second, I assign grades according to a percentile scale, where A = [83,100], AB = [65,83), B = [45,65), BC = [25,45), C = [6,25), D = [3,6), F = [0,3). (In other words, if you perform better than 83% of the class, then you’ll receive an A). Your overall grade in the class is the higher of these two grades.

I strive to make all of the grading transparent and fair.  If you are unhappy with the way a problem has been graded, I encourage you to discuss it with me, but you must bring the concern to me within 7 days of when you were first able to view the graded problem set or quiz.

Learning Outcomes

Following the completion of this course, students will be able to:

• Interpret tables, graphs, and statistics used for describing data
• Apply probability theory to characterize random variables and determine the likelihood of uncertain events
• Estimate population parameters using point and interval estimators
• Evaluate and describe the properties of an estimator
• Test theories about population parameters by determining an appropriate test statistic, implementing a formal hypothesis test, and interpreting the outcome
• Use statistical software to apply these statistical techniques to the analysis of economic data

Credits

The credit standard for this course is met by an expectation of a total of 180 hours of student engagement with the course learning activities (at least 45 hours per credit), which includes watching video lectures, completing problem sets, working on practice problems, taking exams, and other student work as described in the syllabus.

Students with Disabilities

If you have approval from the McBurney Center for disability-related accommodations, please contact me to discuss how these accommodations will be implemented for this course.  This should be done as soon as possible, and no later than two days before the first weekly quiz.

Grievance Procedure

The Department of Economics has developed a grievance procedure through which you may register comments or complaints about a course, an instructor, or a teaching assistant.  The Department continues to provide a course evaluation each semester in every class.  If you wish to make anonymous complaints to an instructor or teaching assistant, the appropriate vehicle is the course evaluation.  If you have a disagreement with an instructor or a teaching assistant, we strongly encourage you to try to resolve the dispute with him or her directly.  The grievance procedure is designed for situations where neither of these channels is appropriate.

If you wish to file a grievance, you should go to room 7238 Social Science and request a Course Comment Sheet.  When completing the comment sheet, you will need to provide a detailed statement that describes what aspects of the course you find unsatisfactory.  You will need to sign the sheet and provide your student identification number, your address, and a phone where you can be reached.  The Department plans to investigate comments fully and will respond in writing to complaints.

Your name, address, phone number, and student ID number will not be revealed to the instructor or teaching assistant involved and will be treated as confidential.  The Department needs this information, because it may become necessary for a commenting student to have a meeting with the department chair or a nominee to gather additional information.  A name and address are necessary for providing a written response.

Misconduct Statement

Academic Integrity is critical to maintaining fair and knowledge based learning at UW Madison. Academic dishonesty is a serious violation: it undermines the bonds of trust and honesty between members of our academic community, degrades the value of your degree and defrauds those who may eventually depend upon your knowledge and integrity.

Examples of academic misconduct include, but are not limited to: cheating on an examination (copying from another student's paper, referring to materials on the exam other than those explicitly permitted, continuing to work on an exam after the time has expired, turning in an exam for regrading after making changes to the exam), copying the homework of someone else, submitting for credit work done by someone else, stealing examinations or course materials,  tampering with the grade records or with another student's work, or knowingly and intentionally assisting another student in any of the above. Students are reminded that online sources, including anonymous or unattributed ones like Wikipedia, still need to be cited like any other source; and copying from any source without attribution is considered plagiarism.

The Dept. of Economics will deal with these offenses harshly following UWS14 procedures (http://students.wisc.edu/saja/misconduct/UWS14.html):

1. The penalty for misconduct in most cases will be removal from the course and a failing grade.
2. The department will inform the Dean of Students as required and additional sanctions may be applied.
3. The department will keep an internal record of misconduct incidents. This information will be made available to teaching faculty writing recommendation letters and to admission offices of the School of Business and Engineering.

If you think you see incidents of misconduct, you should tell your instructor about them, in which case they will take appropriate action and protect your identity. You could also choose to contact our administrator (Tammy Herbst-Koel: therbst@wisc.edu) and your identity will be kept confidential.