ECON 311: Analytical Tools for Economists
Syllabus
Course Information
Semester: Fall 2025
Delivery: Online; TR 1:30 PM - 2:45 PM (Zoom Link)
Office Hours: Wednesday 03:00 PM - 05:00 PM (or by appointment)
Course Description
In this course, students will learn how to build statistical models and use data to answer real-world questions. Through hands-on work with modern statistical software, students will learn to visualize, estimate, interpret, evaluate, and articulate relationships in data. Students will obtain real, tangible skills such as experience with statistical software as well as develop their economic intuition.
Prerequisites: ECON 202S or equivalent.
Textbooks and Other Materials
There is no required text for this course.
Required Software
As this course focuses on the learning and application of econometric techniques, a computer or laptop with R and RStudio installed is required for this course. Students can obtain the latest version of R from r-project.org. Students can obtain a free version of R-studio from posit.co. While students can directly code in R, it is recommended that student use RStudio to facilitate interactions with the R language. Students will also install numerous open source packages throughout the course. Students need not install this software prior to beginning the course.
Course Learning Objectives
- Develop R programming skills in RStudio.
- Interpret, evaluate, and visualize relationships in data.
- Estimate econometric models with R.
Course Schedule
Below is a schedule for course topics with corresponding assignments. See Grading Policy below for due dates.
Grading Policy
The evaluation for this course consists of homework assignments and a final project (in addition to checkpoints throughout the semester). The final grade is comprised of the following elements:
Grades will be determined by the sum of points earned, and then converted using this table:
| Letter | Minimum | Maximum |
|---|---|---|
| A | 467 | 500 |
| A- | 450 | 466 |
| B+ | 433 | 449 |
| B | 417 | 432 |
| B- | 400 | 416 |
| C+ | 383 | 399 |
| C | 367 | 382 |
| C- | 350 | 366 |
| D+ | 333 | 349 |
| D | 317 | 332 |
| D- | 300 | 316 |
| F | 0 | 299 |
Except for grades of “Incomplete”, all grades are considered final when reported by a faculty member at the end of a semester. A change in grade may only be requested when a calculation, clerical, administrative, or recording error is discovered in the original assignment of a course grade or when a decision is made by the faculty member to change the course grade because of the disputed academic evaluation procedures.
Grade changes necessitated by a calculation, administrative, or recording error must be reported within a period of six months from the time the grade is awarded. No grade may be changed as the result of a re-evaluation of a student’s work or the submission of supplemental work following the close of a semester.
Homework
Homework assignments will contain questions about statistical theory and practice, in addition to programming exercises. Students are expected to submit their assignments on Canvas. Submissions should be .html files generated using each assignment’s associated template. Please see the following sections about Artificial Intelligence and Revising Assignments for additional details.
Note: It is likely that students will have to venture out onto the internet by themselves to find solutions to homework questions.
Final Project
The goal of the final project is to write a research paper using the tools covered in this course. Projects will demonstrate students’ competency using R and their ability to articulate technical concepts. Projects will be uploaded to, or embedded within, a student’s ePortfolio by the end of the course. See the Final Project’s page for more information.
It should be noted that, including the project checkpoints, the final project is a large portion of your final grade. Therefore, it’s important to keep up with the checkpoints and be in communication with me about your project throughout the course.
ePortfolio
In an effort to help students reflect on and synthesize their learning experiences, as well as demonstrate their skills to potential employers, certain courses taught by faculty in the Economics department will require the creation of, or addition to, an ePortfolio. Given the status of this course as the capstone of the Economics major, this course will contain an ePortfolio component.
Final projects will be submitted via Canvas and uploaded to each student’s ePortfolio. The extent to which students use their ePortfolio is ultimately up to them, but having this project online and visible should help to differentiate them from competing job seekers. As a note, all material generated in this course will be portable .html files that can easily be uploaded to ePortfolios.
Online ePortfolio resources for ODU students can be found at odu.edu/asis/eportfolio.
Disclaimer: this course incorporates various online software and other technologies. Some technologies require you to either create an account on an external site or develop assignment content using them. The content, as well as your name/username or other personally identifying information may be publicly available as a result. While the purpose of these assignments is to engage with technology as a means for representing the content we are covering in class, please see me for an alternative activity if you object to potentially sharing your account, name, or other content you create in these technologies.
Final Exam
Students will be given an oral final exam during the dedicated time period. The exam schedule can be found here. Exams will be a mix of questions pertaining to the course material and specific questions pertaining to the student’s final project.
Incomplete Grades
A grade of “I” indicates assigned work yet to be completed in a given course, or absence from the final examination, and is assigned only upon instructor approval of a student request. The “I” grade may be awarded only in exceptional circumstances beyond the student’s control. The “I” grade becomes an “F” if not removed by the day grades are due for following term based on specific criteria: Incomplete, Withdraws and Z grades.
Course Policies
Communication
Students should feel welcome to contact me via email (acardazz@odu.edu) or drop by my office. Generally, I respond to well-crafted emails within 48 business hours. I have an ‘open door’ policy for student questions and strongly encourage students to communicate with me. Of course, since this is an online course, I will be available over Zoom as well.
Students should take the time to craft complete, professional emails. The more information that you can provide about a question or problem, the more likely that my response will be helpful. Avoid non-professional language and practice communicating in the corporate workplace. Emails that are unprofessional will be returned with no action. There are many guides on how to compose a professional email which you can easily find online.
Attendance and Participation
Given this is a synchronous course, students are expected to show up for class. Recordings of lectures will only be provided to students who attend a substantial portion of meetings unless previously negotiated. Aside from this, there will be no points taken or given based on attendance/participation as students are responsible for their own learning.
Late Assignments
All due dates are firm. Late submissions of any assignment will receive a score of zero unless discussed at least forty-eight hours prior to the deadline. Special circumstances that are communicated in advanced will be handled on a case by case basis.
Plagiarism
Plagiarism and turning in work that is not yours is grounds for being assigned a zero on an assignment, is a violation of the University Honor Code, and could result in failure in the course and/or academic action by the university.
Artificial Intelligence
You are currently enrolled in a course you can think of as a simultaneous introduction to both econometrics and the programming language R. You are enrolled in said course during a time in which artificial intelligence (AI) is booming. It is quite possible that AI will end up being the most transformative technology since the internet, and ignoring it would be foolish. As we get started in this course, I want to provide a few additional thoughts on AI and its use in this course.
As I am sure you understand by now, education is having to rapidly adjust to AI. This means that much of what previously worked, especially with regards to assessment, no longer does. At this point, the only path forward is to embrace the idea that AI will forever be part of the “toolkit,” much like how calculators, spell-check, and search engines are. Therefore, cautious AI use is allowed in this course. Reckless AI use, much like reckless use of other tools (e.g., copying and pasting text from Wikipedia and claiming it as your own), remains banned.
What constitutes appropriate AI use? Appropriate AI use is collaborative rather than substitutive. Using AI to help you understand why your code is not working is appropriate (collaborative), but having it write the code for you is not and may be considered reckless (substitutive). When determining the appropriateness of their AI use, students may find it helpful to ask themselves whether someone with no training, but access to an AI, could have produced the same thing. If the answer is yes, then the student has not added any value, and their AI use was substitutive. Students may also frame this question through the lens of employment and ask themselves whether someone would hire them for what they produced, or if this is instead something an AI could produce (for much a lower cost)? Companies are chomping at the bit to cut labor costs by replacing employees with AI; do something that makes this a difficult decision for them.
To encourage students to use AI collaboratively (or not at all), students abiding by this policy may be given the opportunity to resubmit homework. See the Revising Assignments section of the Syllabus for more details. On the other hand, students who are suspected of reckless AI use will be given a grade of zero for the specific questions unless they can prove otherwise (via a live, oral explanation of their answers recorded over Zoom, or a link to an AI chat).
Lastly, in the interest of transparency, detecting AI use is in fact not terribly difficult (albeit imperfect). Just like how individuals have particular ways of writing and speaking, they also have particular ways of coding. This can be the way they use spaces, capitalization, comments, etc. Each student in this course will develop their own specific way of writing/structuring code that looks and feels like their own. Moreover, when you learned to write sentences, you probably made simple mistakes like starting with “but” or “and,” or forgot to capitalize a proper noun, etc. As you are learning to code, you will make the programming version of these mistakes. Your use of space will be inconsistent, you will forget to use comments, and your code will sometimes be inefficient or verbose. All of these things are totally OK and part of the learning process. On the other hand, the code AI will generate will make it look like you have been coding for years. AI will use functions and libraries that do not appear in the course notes, it will provide perfect documentation, and adhere to obscure style guides. I have seen it happen time and time again, so it’s easy to spot.
Directions for using AI
If students would like to use AI, students are required to do so with “guardrails,” so to speak. Students will initialize a total of two (2) chats within ChatGPT by using prompts provided to them by the instructor. The first chat will be used to talk with the AI about course material and homework while the second chat will be used specifically for their final project. Students will need to share links to these chats with the instructor, hence the “guardrails.” Clever students might think to appease the instructor by setting up these chats but then doing everything else in chats on the side. While this is certainly possible, it is unlikely to be beneficial to the student. First, if reckless AI use is suspected without any evidence to the contrary (e.g., documented in the respective chats), the student will receive a zero for their work until evidence can be provided (see above). Second, sticking to only two chats throughout the entire course provides the advantage that the AI will learn alongside you and be able to observe your entire conversation history (as opposed to starting fresh each time). This eliminates the need to re-explain things to the AI, and should make the output more consistent. So long as AI use is documented and not simply asking for answers, using AI is approved (even encouraged).
For example, consider the following good and bad uses of AI:
Good AI Use
Below, I have pasted a homework problem that I am struggling with. I cannot seem to figure out how to do XYZ, because my code keeps giving me an error. Can you help me fix this error?
or
Below, I have pasted a homework problem that I am struggling with. So far, I have been able to do ABC, but am getting stuck at XYZ. Can you help me with the next step?
Bad AI Use
Below, I have pasted a homework problem that I am struggling with. Can you give me the answer?
or
Below, I have pasted a homework problem that I am struggling with. Please walk me through it.
Please note the special AI directions for the Final Project. See the Final Project’s page for more information.
Steps to Set Up the AI
Sign up for, or log into, an OpenAI account.
Start a new chat with the following prompt
This prompt is meant to initialize you as a helper for a student taking an introduction to econometrics course. The course leans towards the applied side of econometrics so students will also be learning (base, not tidyverse) R simultaneously. As a helper, you may help/advise the student, but may not do things for the student. This chat will be used throughout the semester as the student works through the lecture material and homework assignments. At the beginning of each of your messages, always put the current date and time [YYYY-MM-DD H:i] (use eastern time). The student will now begin interacting with you.
Note that on the sidebar to the left, a new chat will appear. Every time you want to use AI for this course, navigate to this specific chat.
Next, click on the share button button in the upper right of the screen. For the first time, it should say “Create link,” but each time after that it should say “Update link.” You must copy-and-paste this link into each of your homework assignments. You will have to re-share/update the link each time you are submitting a HW.
Revising Assignments
Students may occasionally be invited to revise their answers to questions on certain assignments for half credit on what was initially marked as incorrect. Note that blank answers, what I deem to be “low effort” answers, or answers that have been flagged for reckless AI use will not be invited for revision. Requests from students to revise their work will be promptly declined. To be clear, the purpose of this policy is to reduce the relative benefits of reckless AI use or other forms of academic dishonesty. The hope is that the potential to revise high effort answers encourages students to submit high effort answers, even if they are not completely correct.
Course Disclaimer
The course schedule and activities are subject to change. Changes will be posted as Announcements in Canvas. All instructional materials and homework assignments can be found here.
University Policies
Code of Student Conduct and Academic Integrity
The Office of Student Conduct & Academic Integrity (OSCAI) oversees the administration of the student conduct system, as outlined in the Code of Student Conduct. Old Dominion University is committed to fostering an environment that is: safe and secure, inclusive, and conducive to academic integrity, student engagement, and student success. The University expects students and student organizations/groups to uphold and abide by standards included in the Code of Student Conduct. These standards are embodied within a set of core values that include personal and academic integrity, fairness, respect, community, and responsibility.
Honor Pledge
By attending Old Dominion University, you have accepted the responsibility to abide by the Honor Pledge:
I pledge to support the Honor System of Old Dominion University. I will refrain from any form of academic dishonesty or deception, such as cheating or plagiarism. I am aware that as a member of the academic community it is my responsibility to turn in all suspected violations of the Honor Code. I will report to a hearing if summoned.
Discrimination Policy
The purpose of this policy is to establish uniform guidelines to promote a work and education environment that is free from harassment and discrimination, as defined below, and to affirm the University’s commitment to foster an environment that emphasizes the dignity and worth of every member of the Old Dominion University community. The Discrimination Policy details the process to address complaints or reports of retaliation, as defined by this policy.
Diversity and Inclusion
The Division of Student Engagement & Enrollment Services values the uniqueness of our Monarch community. The word “engagement” reflects our commitment to embrace the differences in our cultural backgrounds, perceptions, beliefs, traditions, world views, socio-economic status, cognitive and physical abilities.
We will strive to serve as the pre-eminent model for engaging every student to achieve their own success. Our core values are fueled by our responsibility and actions toward community development and engagement, cultural competence and understanding, physical and mental wellness and inclusion for every member of ODU. We will embrace our greatest strength - the diverse composition of our student body and workforce. For more information regarding diversity and inclusion, please visit the Office of Intercultural Relations.
Educational Accessibility and Accommodations
Old Dominion University is committed to ensuring equal access to all qualified students with disabilities in accordance with the Americans with Disabilities Act. The Office of Educational Accessibility (OEA) is the campus office that works with students who have disabilities to provide and/or arrange reasonable accommodations.
The Accommodations for Students with Disabilities define the procedures used to accommodate student with disabilities. Students are encouraged to self-disclose disabilities that the Office of Educational Accessibility has verified by providing Accommodation Letters to their instructors early in the semester in order to start receiving accommodations. Accommodations will not be made until the Accommodation Letters are provided to instructors each semester
University Email Policy
With the increasing reliance and acceptance of electronic communication, email is considered an official means for University communication. Old Dominion University provides each student an email account for the purposes of teaching and learning, research, administration, and service. It is the responsibility of every eligible student to activate MIDAS, the Monarch Identification and Authorization System, to obtain email access. It is important that all students are aware of the expectations associated with email use as outlined in the Student Email Standard. The email account provided by the University is considered to be an official point of contact for correspondence. Students are expected to check their official e-mail account on a frequent and consistent basis in order to stay current with University communications. Mail sent to the ODU email address may include notification of University-related actions, including academic, financial, and disciplinary actions. For more information about student email, please visit Student Computing.
Withdrawal
A syllabus constitutes an agreement between the student and the course instructor about course requirements. Participation in this course indicates your acceptance of its teaching focus, requirements, and policies. Please review the syllabus and the course requirements as soon as possible. If you believe that the nature of this course does not meet your interests, needs or expectations, if you are not prepared for the amount of work involved – or if you anticipate assignment deadlines or abiding by the course policies will constitute an unacceptable hardship for you – you should drop the course by the drop/add deadline, which is listed in the ODU Schedule of Classes. For more information, please visit the Office of the University Registrar.
Privacy of Student Information
Old Dominion University recognizes its duty to uphold the public’s trust and confidence, not only in following laws and regulations, but in following high standards of ethical behavior. Members of the Old Dominion University community are responsible for maintaining the highest ethical standards and principles of integrity. The Code of Ethics is a set of values-based statements that demonstrate the University’s commitment to this goal. The Privacy of Student Information details Family Educational Rights & Privacy Act (FERPA), along with other information regarding privacy.
Other Academic Policies
Please see the following link for other academic policies at the university level: https://catalog.odu.edu/undergraduate/policies/academic-policies/