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程序代写案例-CED 6983
时间：2021-03-27
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Course Syllabus
Course Information
Course Number CED 6983
Course Name Business Fluctuations and Economic Forecasting
CRN 23597
Quarter / Year
Term Length 6 Weeks
Start / End Dates Mar 01, 2021 - Apr 10, 2021
Credit Hours 3.0
Course Format Virtual
Location
Instructor Information
Full Name: Mikhail Oet, PhD
NEU Email Address: m.oet@northeastern.edu
Office Hours: Email me to schedule an appointment
Second Point of Contact
In the event that some concern about the course arises and is not addressed by the instructor, please
contact:
Full Name: Fiona Creed, PhD, Acting Facuty Director, Global and Social Enterprise Domain
NEU Email Address: f.creed@northeastern.edu
If for any reason you wish to express a concern about anything that may impact your success in a course,
first speak directly with your Instructor. If you need additional support, please contact your Academic
Advisor.
Course Delivery
This course will be delivered using the virtual learning modality and I will be teaching remotely.I will
schedule weekly meetings using a video platform, usually Zoom or Teams, for students who would like to
join me synchronously. There is no requirement to participate synchronously, but at least asynchronous
participation and engagement is required. Students joining synchronously will be able to ask questions,
discuss, and interact with me and other students in real time. I will also be available for virtual office
hours on request by email.
Technical Requirements
Courses are available on Northeastern University’s Canvas at the following link:
http://canvas.northeastern.edu. Canvas Technical support and resources including 24/7 phone (1-833-450-
3937), and chat can be found on the help icon in Canvas. Northeastern Technical support can be accessed at
617-373-4357 (xHELP) or help@northeastern.edu.
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Each student is responsible for their access to the internet for purposes of this course and for research. Internet
access is a required component of this course and will not be accepted as an excuse for missed work. If you
know that you will be traveling, then make sure you plan accordingly.
Note regarding e-mail/voicemail: If you e-mail, please include your name and class title. Please allow up to 48
hours for an email reply. If you leave a voicemail, please remember to include your name, class title, and phone
number.
Course Prerequisites
• none
Course Description
This course provides students with the latest developments and forecasting methods in the analytics of
business fluctuations. The course emphasizes R language as means of economic data analysis and
provide students hands-on opportunities to deepen their understanding of methods of forecasting of
macroeconomic activity. Students are guided through the experiential case studies on macrofinancial
fluctuations from single equation to simultaneous equations systems (exponential smoothing,
forecasting with ARIMA models, Principal Component/Factor Analysis, Random forest analysis, trend /
cycle decomposition, FAVAR, global modelling).
Course Materials
Course Text(s)/Software/Tools
• Students are required to access Northeastern Canvas at http://canvas.northeastern.edu
Required Text
1. (H), R.J. Hyndman, G. Athanasopoulos, Forecasting Principles and Practice, available online
https://www.otexts.org/fpp3
2. (HW), J.E. Hanke, D.W. Wichern. (2009). Business Forecasting, 9th Edition, Pearson
(Ordering information: 1. Pearson, 2. Amazon, 3. NEU Bookstore)
3. (K), E. Kacapyr, Economic Forecasting, the state of the art, 1996 (Ordering information: 1.
Routledge, 2. Amazon, 3. NEU Bookstore)
4. (T), L. Tvede. Business Cycles: History, Theory and Investment Reality, 3rd Edition (Wiley),
2006 (Ordering information: 1. Wiley, 2. Amazon, 3. NEU Bookstore)
• Additional reading materials will be provided by instructor on Canvas.
Laboratory Materials:
5. https://www.datacamp.com/courses/free-introduction-to-r
6. HarvardX: PH125.1x, Data Science: R Basics, https://courses.edx.org/courses/course-
v1:HarvardX+PH125.1x+1T2018/course/
7. IMF Macroeconomic Forecasting, Archived class, https://www.edx.org/course/macroeconometric-
forecasting-imfx-mfx-0
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Recommended Texts
• Sanz, I. P. (2019). Machine Learning with R Quick Start Guide: A beginner's guide to
implementing machine learning techniques from scratch using R 3.5. Packt Publishing Ltd.
• A. Garratt et al., Global and National Macroeconometric Modelling: A Long-Run Structural
Approach, 2006
• Bomhoff, E. J. (1994). Financial forecasting for business and economics. Academic Press.
• A.A. Beaujean, Latent Variable Modeling Using R, 2014
• W.H. Finch, Jr. and B.F. French, Latent Variable Modeling with R, 2015
Required Software
• R software
Recommended Software
o EViews, http://register1.eviews.com/Lite/
Tools
This course contains audio-visual material, and, in some instances, you may be asked to participate in
audio-based activities, such as a Voice Discussion Board. A headset (headphones plus microphone) will
allow you to hear and record audio. The Logitech ClearChat Comfort USB Headset, or the Plantronics
Audio 470 or 500, or comparable brands/models, are recommended. Headsets can be purchased from
online vendors such as amazon.com, bestbuy.com, or newegg.com. This course may also require a
webcam. If your computer does not have an integrated webcam, webcams can be purchased at online
vendors such as amazon.com.
Program Learning Outcomes (PLOs)
Financial & Economic
Analysis/Data Analytics
Economics Knowledge
Base
Entrepreneurship/Intellec
tual Agility
Communication/Global
PLO 1 PLO 2 PLO 3 PLO 4
Use conceptual and
mathematical tools to
estimate economic
relationships such as
fluctuations in
employment, prices, and
economic growth.
Develop a coherent
framework for analyzing
the determination of
microeconomic and
macroeconomic variables
based on related theories
and models.
Design and implement a
project that applies
economic theories to
business and public policy
issues.
Develop a formal
proposal, real or
hypothetical, addressing a
global intercultural
communication challenge
in the field of commerce
and economic
development that has not
been adequately
addressed.
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SAIL Baseline Mapping
Enter 5 for Central, 4 for Significant, 3 for Moderate, 2 for Minimal, 1 for Potential, or 0
for None
Enter 1 for Passive
Engagement, 2 for Active
Engagement, or 3 for
Generative Engagement
Social
Consciousness
& Commitment
Global
Mindset Intellectual Agility
Personal &
Professional
Effectiveness
Well-
Being Level of Engagement
4 4 4 4 3 3
Course Learning Outcomes
Based on satisfactory completion of this course, by the end of the class students will be able to:
CLO1: History of modern business fluctuations
CLO2: Business cycle theories
CLO3: Business fluctuations and asset prices
CLO4: Exploring and visualizing time series
CLO5: Forecasting with exponential smoothing
CLO6: Forecasting with ARIMA models
CLO7: Advanced methods of forecasting
CLO8: Dimensionality reduction, Principal component, and Factor analysis
CLO9: Identification of critical episodes
CLO10: Tree-based methods and Random Forest.Assess the impact of macro-shocks on capital markets
with correlation analytics
Expectations
• Workload
o Students should expect 3 hours per week of classroom-related discussion and asynchronous
weekly learning plus a minimum of 9 hours per week of out-of-class student work for this 6-
week course.
o APA citations
Attendance Policy
Students are required to attend all scheduled classroom sessions virtually (synchronously or
asynchronously). Students are required to engage with all posted material. Student engagement with
the classroom session material and the weekly posted material is tracked. Absence of engagement with
the classroom sessions and the weekly instructional materials results in loss of score allocated for the
weekly classroom activity.
Policy on late work
A deduction of 20% percent will be made for each day (counted as any portion of a 24-hour period)
that an assignment is late. Late submissions for assignments due by 11:59 PM EST Thursday will not be
accepted after 5 PM EST Friday. Otherwise, work will no longer be accepted 3 days after the specified
deadline, unless specific arrangements have been made with the instructor. With prior permission
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only, any request for an exception to the late submission policy needs be supported by with a signed
doctor’s note. If an extension is granted, all missing assignments are expected to be submitted within 1
week of the termination of the period covered by the doctor’s note.
Policy on early submissions
Early submissions are encouraged. Draft materials received at least 24 hours before the deadline (the
in-advance-submission) will receive feedback and suggestions, allowing for improved final submission
before the deadline. Only the last submission received before the deadline will be graded.
Course Methodology
Each week, you will be expected to:
• Review the week's learning objectives
• Complete all assigned readings
• For each Reading Text Chapter assigned, create a PowerPoint slide summarizing the reading and
submit by email by due date (generally two days before next class) a minimum of one slide (per
chapter).
• Complete all lecture materials for the week: View all assigned videos and/or PowerPoint slides
(synchronously or asynchronously).
• Participate in the ongoing Discussion Board/Google document activities.
• Complete and submit all assignments and project by the due dates.
• Modelling and laboratory assignments: as assigned.
Participation/Class Discussion Board/Team Google document/Shared Google drive
Note: the schedule below is a typical schedule but may be modified to accommodate increased or
decreased assignment load during a specific week. Please consult instructions in the weekly
“Assignment” section on Canvas.
Participation on the Class Discussion Board/Team Google document/Shared Google drive is an integral
part of any online learning community. Each week students must post at least one primary response
(answering a discussion question posted by the instructor) and two secondary responses (responses to
other students’ posts). Participation in Discussion Board/Team Google document is worth 10% of the
total course grade. All postings are expected to be professional in tone, clear, comprehensible,
competently produced and delivered, and their content should reflect an understanding of at least the
lectures and readings assigned. All responses are required to be substantive and related to the weekly
topic(s) under discussion. They will be evaluated solely based on clarity and originality of posts, as well
as the degree to which peers' learning is enriched by those comments and posts. Posts will not be
evaluated based on frequency or length. In other words, quality of the posts is more important than
quantity of posts.
The Class Discussion Board and the Team Google document are spaces for academic exchanges. As a
result, you must check for proper and exacting punctuation, spelling, and grammar. In addition, you
must reference all outside sources in correct citation format. It is crucial that all participants maintain a
high regard for proper decorum in the Class Discussion Board/Team Google Document. A grading rubric
for Discussion Board/Team Google document responses is provided.
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Please treat your classmates and the instructors with the utmost respect. Inappropriate posts will be
removed immediately. The instructor reserves the right to penalize students for repeated violations of
the participation policy within a course.
In the Class Discussion board/Team Google document and in class, high quality contributions advance
the class discussions and do not simply summarize the material that was assigned. Quality
contributions consider not only the instructor’s questions but also your classmates’ contributions.
Communication/Submission of Work
Submissions shall be made through one of three possible means, as specified in a particular assignment:
1. Class Discussions submissions need to be made in the relevant location in Canvas.
2. Data, all analysis, and models used in the project need to be uploaded to the relevant Team
subfolder in a shared Google drive
3. Team Google document needs to be shared in the respective team folder of the shared Google
drive.
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Evaluation Standards
GRADING RUBRIC: Discussion Board /Team Google document Participation
Weight Criteria
EXCEEDING
STANDARDS
100%
MEETING
STANDARDS
80%
APPROACHING
STANDARDS
50%
BELOW
STANDARD
25%
25% Comprehension
Explains key concepts in
one's own words and
illustrates understanding
of material via unique
examples and personal
perspective.
Explains key concepts in
one's own words and
illustrates understanding
of material by citing
examples.
Able to explain key
concepts in one's own
words.
Unable to put key
concepts in one's own
words.
25% Engagement
Adds substantive
information, asks
meaningful questions to
peers, and provides
substantive responses.
Adds substantive
information to the
discussion and asks
meaningful questions to
peers.
Adds substantive
information to the
discussion.
Does not add substantive
information to the
discussion.
25% Connections
Integrates learned
concepts by making
strong connections to
personal experience or
previous understanding.
Integrates learned
concepts by making
explicit connections to
personal experience or
previous understanding.
Integrates learned
concepts by making
implicit connections to
personal experience or
previous understanding.
Does not integrate
learned concepts by
making connections to
personal experience or
previous understanding.
25% Writing
Writes clearly and
concisely with no errors
related to organization,
grammar, style, and
citations.
Writes clearly and
concisely with some
errors related to
organization, grammar,
style, and citations.
Writes clearly with very
few errors related to
organization, grammar,
style, and citations.
Does not write clearly
with many errors related
to organization, grammar,
style, and citations.
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GRADING RUBRIC: Written Communication
Criteria Exceeding Standards Meeting Standards Approaching Standards Below Standards
CONTEXT 100% 80% 50% 25%
Weight 20%
Demonstrates a thorough
understanding of context,
audience, and purpose that
is responsive to the
assigned task(s) and
focuses all elements of the
work.
Demonstrates adequate
consideration of context,
audience, and purpose
and a clear focus on the
assigned task(s) (e.g., the
task aligns with audience,
purpose, and context).
Demonstrates awareness
of context, audience,
purpose, and to the
assigned tasks(s) (e.g.,
begins to show awareness
of audience's perceptions
and assumptions).
Demonstrates minimal
attention to context,
audience, purpose, and to
the assigned tasks(s) (e.g.,
expectation of instructor
or self as audience).
CONTENT 100% 80% 50% 25%
Weight 20%
Uses appropriate, relevant,
and compelling content to
illustrate mastery of the
subject, conveying the
writer's understanding, and
shaping the whole work.
Uses appropriate,
relevant, and compelling
content to explore ideas
within the context of the
discipline and shape the
whole work.
Uses appropriate and
relevant content to
develop and explore ideas
through most of the work.
Uses appropriate and
relevant content to
develop simple ideas in
some parts of the work.
CONVENTIONS 100% 80% 50% 25%
Weight 20%
Demonstrates detailed
attention to and successful
execution of a wide range
of conventions particular to
a specific discipline and/or
writing task (s) including
defining terms,
organization, content,
presentation, formatting,
and stylistic choices
Demonstrates consistent
use of important
conventions particular to
a specific discipline
and/or writing task(s),
including defining terms,
organization, content,
presentation, and stylistic
choices
Follows expectations
appropriate to a specific
discipline and/or writing
task(s) for basic
organization, content, and
presentation.
Attempts to use a
consistent system for
basic organization and
presentation.
SOURCES 100% 80% 50% 25%
Weight 20%
Demonstrates skillful use of
high- quality, credible,
relevant sources to develop
ideas that are appropriate
for the discipline and genre
of the writing
Demonstrates consistent
use of credible, relevant
sources to support ideas
that are situated within
the discipline and genre
of the writing.
Demonstrates an attempt
to use credible and/or
relevant sources to
support ideas that are
appropriate for the
discipline and genre of
the writing.
Demonstrates an attempt
to use sources to support
ideas in the writing.
MECHANICS 100% 80% 50% 25%
Weight 20%
Uses graceful language that
skillfully communicates
meaning to readers with
clarity and fluency and is
virtually error free.
Uses straightforward
language that generally
conveys meaning to
readers. The language in
the portfolio has few
errors.
Uses language that
generally conveys
meaning to readers with
clarity, although writing
may include some errors.
Uses language that
sometimes impedes
meaning because of
errors in usage.
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Grading
Graduate Programs Final Grading Scale
95-100% A 87-89.9% B+ 77-79.9% C+ 69.9% or below F 84-86.9% B 74-76.9% C
90-94.9% A- 80-83.9% B- 70-73.9% C-
Grade Breakdown
Title Description Grade (Pts or %)
1 Discussions 10%
2 Homeworks 50%
5 Final Project 40%
Total 100%
Course Schedule
Week Topic Reading Assignments CLO SLO
1 Discovery of
business
cycles
• Money as wealth: John Law and Banque
Royal
• Money supply: France 1719-1720
• The birth of central banking: Quesnay,
Cantillon, Smith, Thorton, Say, Ricardo, Mill
• Pioneers of business cycle studies: Babbage,
Juglar, Walras, Pareto, Jevons, Newcomb,
Edgeworth
• Classical levers of business cycles: asset
prices and psychology (Marshall, Pigou),
capacity building (Hobson, Tugan-
Baranovsky, Catchings and Foster, Clark),
technological innovation (Spiethoff), interest
rates (Wicksell, Kassel, Roberston, Hawtrey)
• Classical empirical studies of business cycles:
Mitchell, Burns, Kitchin, Kuznets, Kondratieff
• The emergence business cycle forecasting:
Fisher, Babson.
• Policy responses: Keynes, Hayek
• Reading 1: (T) Ch. 1 , 2, 3, 4, 6, 7, 8, 9, 10
• Problem Sets: Complete and submit homework 1:
o Create and post 1 slide for each chapter in Reading
1
• Discussion Board Activity:
o Review: instructor and classmate slides for reading
1
o Post answers to instructor’s question(s) by
Thursday and questions/ comments in response to
your peers’ postings by Sunday
• Classroom Activity
CLO 1
CLO 2
SLO 1
SLO 2
2 First business
cycle theories:
the observed
and the
unobservable
• Entrepreneurship’s role in business
fluctuations: Shumpeter
• Inherent financial instability: Minsky,
Kuznets, Friedman
• Mathematical dynamics and econometric
forecasting: Tinbergen, Frisch, Cobwebb
theorem, multiplier, accelerator, lags,
feedbacks
• Neoclassical synthesis and general
equilibrium: Arrow, Debreu
• Real business cycle theories: Kydland,
Prescott
• Macroeconometric Models: Klein
• Inventory cycles: Metzler
• Fat tails: Hurst, Mandelbrot
• Complexity and chaos: May, Lorenz,
Feigenbaum
• Modeling paradigms: econometrics, system
dynamics, artificial intelligence
• Reading 2: (T) Ch. 11, 12, 13, 14, 15, 16, 17
• Problem Sets: Complete and submit homework 2:
o Create and post 1 slide for each chapter in Reading
2
• Discussion Board Activity:
o Review: instructor and classmate slides for reading
2
o Post answers to instructor’s question(s) by
Thursday and questions/ comments in response to
your peers’ postings by Sunday
• Classroom Activity
CLO 3
CLO 4
SLO 2
SLO 3
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3 Introduction
to R
• Presentation of advanced correlation maps
visualising interconnectivity of markets
• Focus on Value at Risk analytics and outlier
detection
• Development of early warning signals
through monitoring of interconnected
market dynamics and visual
• Statistical identification of hidden patterns
in complex data
• Hands-on use of dashboards for Case Studies
(e.g. US Housing Bubble and Crisis)
• Review Laboratory materials (5) Intro, Sections 1, 2 , 3, 4,
exercise slides/screenshots/text)
• Problem Sets: Complete and submit Homework 3
(Laboratory assignment 1)
• Problem Sets: Complete and submit Homework 4
(Laboratory assignment 2)
• Discussion Board Activity: Post answers to instructor’s
question(s) by Thursday and questions/ comments in
response to your peers’ postings by Sunday
o Discussion questions:
https://www.datacamp.com/courses/free-
introduction-to-r
• Classroom Activity
CLO 1
CLO 2
CLO 3
CLO 4
SLO 3
SLO 4
SLO 5
4 Stress Testing
Correlation
Networks
• Focus on financial markets as a complex
system with numerous measurable
interdependencies
• Production of 'what if' scenarios to predict
movements of markets under stress
• Stress testing correlation structures
• Hands-on use of interactive dashboards in
relation to Case Studies (e.g. Brexit
Referendum and US Presidential Election)
• Reading 1: Economic Forecasting
(K) Ch. 1, 2;`
(H) Ch. 2, 3.
• Reading 2: (K) Ch. 3, 4;
(H) Ch. 7.
• Reading 3: (K) Ch. 5, 6;
(H) Ch. 8.
• Reading 4: (K) Ch. 7, 8;
(H) Ch. 9, 11.
• Problem Sets: Complete and submit homework 4:
o 1 slide ea. for Chapter in Reading 1, Lab Assignment
3 (DataCamp for Classroom, Forecasting in R, Unit
1: Exploring and visualizing time series in R AND
Unit 2: Benchmark methods and forecast accuracy)
o 1 slide ea. for Chapter in Reading 2, Lab Assignment
4 (DataCamp for Classroom, Forecasting in R, Unit
3: Exponential smoothing)
o 1 slide ea. for Chapter in Reading 3, Lab Assignment
5 (DataCamp for Classroom, Forecasting in R, Unit
4: Forecasting with ARIMA models)
o 1 slide ea. for Chapter in Reading 4, Lab Assignment
6 (DataCamp for Classroom, Forecasting in R, Unit
5: Advanced methods)
• Discussion Board Activity:
o Review: slides for readings 1 and 2
o Post answers to instructor’s question(s) by
Thursday and questions/ comments in response to
your peers’ postings by Sunday
• Classroom Activity
CLO 2
CLO 6
CLO 7
SLO 3
SLO 4
SLO 5
5 Applications
of
quantitative
social science
research
methods
• Exploratory methods
o Principal Component and Factor
Analysis
o Latent variables with R
o QCA
o Network analysis
• XN Project activity unit 1
• XN Project activity unit 2
• XN Project activity unit 3
• XN Project activity unit 4
• Problem Sets: Complete and submit homework 4:
o Lab assignment: Complete course record in
https://campus.datacamp.com/courses/machine-
learning-with-tree-based-models-in-r
• Discussion Board Activity:
o Review: slides for XN Project activity units 1, 2, 3, 4
o Post answers to instructor’s question(s) by
Thursday and questions/ comments in response to
your peers’ postings by Sunday
• Classroom Activity
CLO 5 SLO 3
SLO 4
SLO 5
6 Applications
of early
warning
methods
• Confirmatory methods
o Tree-based Methods
o Random Forest
o Early warning systems
o Global modelling
• XN Project activity unit 5
• XN Project activity unit 6
• XN Project activity unit 7
• XN Project activity unit 8
• Discussion Board Activity:
CLO 5
CLO 6
CLO 7
SLO 3
SLO 4
SLO 5
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o Review: slides for XN Project activity units 5, 6, 7, 8
o Post answers to instructor’s question(s) by
Thursday and questions/ comments in response to
your peers’ postings by Sunday
• Classroom Activity
End-of-Course Evaluation Surveys
Your feedback regarding your educational experience in this class is very important to the College of
Professional Studies. Your comments will make a difference in the future planning and presentation of our
curriculum.
At the end of this course, please take the time to complete the evaluation survey at
https://neu.evaluationkit.com. Your survey responses are completely anonymous and confidential. For
courses 6 weeks in length or shorter, surveys will be open one week prior to the end of the courses; for courses
greater than 6 weeks in length, surveys will be open for two weeks. An email will be sent to your HuskyMail
account notifying you when surveys are available.
Academic Integrity
A commitment to the principles of academic integrity is essential to the mission of Northeastern University. The
promotion of independent and original scholarship ensures that students derive the most from their educational
experience and their pursuit of knowledge. Academic dishonesty violates the most fundamental values of an
intellectual community and undermines the achievements of the entire University.
As members of the academic community, students must become familiar with their rights and responsibilities. In
each course, they are responsible for knowing the requirements and restrictions regarding research and writing,
examinations of whatever kind, collaborative work, the use of study aids, the appropriateness of assistance, and
other issues. Students are responsible for learning the conventions of documentation and acknowledgment of
sources in their fields. Northeastern University expects students to complete all examinations, tests, papers,
creative projects, and assignments of any kind according to the highest ethical standards, as set forth either
explicitly or implicitly in this Code or by the direction of instructors.
Go to http://www.northeastern.edu/osccr/academic-integrity-policy/ to access the full academic integrity
policy.
CPS expects independent and original work. Dishonesty and/or carelessness violates fundamental values of an
intellectual and professional community and will be reported to the Office of Student Conduct and Conflict
Resolution (OSCCR) as a violation of the Academic Integrity Policy. To safeguard the integrity of assignments and
programs, your course may use systems such as TurnItIn, which checks written work, and Examity, an online
exam proctoring system. Work that contains academic integrity violations (AIV) will be graded on a case by case
basis. Work displaying AIV may earn a failing grade, a zero, or even result in the instructor assigning the student
a failing grade for the class. Students may not withdraw from a class to avoid the grade penalty for serious
academic integrity violations.
For additional information or for answers to frequently asked questions, please visit:
https://cps.northeastern.edu/academic-resources/academic-integrity
You may also email CPS-AcademicIntegrity@northeastern.edu.
Student Accommodations
The College of Professional Studies is committed to providing equitable access to learning opportunities to
students with documented disabilities (e.g. mental health, attentional, learning, chronic health, sensory, or
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physical). To ensure access to this class, and program, please contact The Disability Resource Center
(http://www.northeastern.edu/drc/) to engage in a confidential conversation about the process for requesting
reasonable accommodations in the classroom and clinical or lab settings. Accommodations are not provided
retroactively so students are encouraged to register with the Disability Resource Center (DRC) as soon as they
begin their program. The College of Professional Studies encourages students to access all resources available
through the DRC for consistent support.
Library Services
The Northeastern University Library is at the hub of campus intellectual life. Resources include over 900,000
print volumes, 206,500 e-books, and 70,225 electronic journals.
For more information, visit http://library.northeastern.edu/.
Wyzant Tutoring Services
Northeastern University's College of Professional Studies is covering the cost of 4 hours of tutoring from Wyzant
to help ensure your success in challenging courses. Tutors on Wyzant have helped thousands of students in 300+
subjects ranging from College Algebra to Academic Writing, Statistical Analysis to Microbiology.Click here to
access your free tutoring through Northeastern University's Wyzant account.
Access your free tutoring using your Northeastern login credentials. Indicate your program, time zone, the
course you'd like support in, and the specific topics or materials you'd like help with.
You'll receive an activation email from Wyzant for Higher Ed. (If you don't see it, check your spam or junk
folders.) From the email, click on the activation button.
Potential tutors will begin reaching out to you. Their messages will be sent to your Northeastern email inbox and
will be accessible via your Wyzant account dashboard.
Respond back to the tutors you believe might be a good fit to schedule an online session when it's convenient
for you — even late at night!
24/7 Canvas Technical Help
For immediate technical support for Canvas, call 1-833-450-3937. You can chat and report an issue to Canvas
technical support right from within Canvas through the Help icon located in the Canvas global navigation.
myNortheastern, e-mail, and basic technical support
Visit the Information Technology Services (ITS) Support Portal
Email: help@northeastern.edu
ITS Customer Service Desk: 617-373-4357 (help)
Catalog
The College of Professional Studies Graduate Catalog is a reference/resource with information about curricula,
resources, and academic and student policies.
For more information, visit http://www.cps.neu.edu/student-resources/.
Diversity and Inclusion
Northeastern University and the and the Office of Institutional Diversity and Inclusion (OIDI) is committed to
equal opportunity, affirmative action, diversity and social justice while building a climate of inclusion on and
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beyond campus. In the classroom, member of the University community work to cultivate an inclusive
environment that denounces discrimination through innovation, collaboration and an awareness of global
perspectives on social justice.
Please visit http://www.northeastern.edu/oidi/ for complete information on Diversity and Inclusion
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TITLE IX
Title IX of the Education Amendments of 1972 protects individuals from sex or gender-based
discrimination, including discrimination based on gender-identity, in educational programs and activities that
receive federal financial assistance.
Northeastern’s Title IX Policy prohibits sex and gender-based discrimination, including sexual harassment,
sexual assault, sexual exploitation, relationship or domestic violence, and stalking. The Title IX Policy refers to
sex and gender-based discrimination as “Prohibited Offenses.” The Title IX Policy applies to the entire
Northeastern community, including students, faculty and staff of all gender identities.
Allegations of Prohibited Offenses can be reported to the Title IX Coordinator within The Office for University
Equity and Compliance at: titleix@northeastern.edu and/or through the Northeastern University Police
Department (NUPD) by phone: for an Emergency 617.373.3333; for Non-Emergency 617.373.2121. Reporting
to NUPD does NOT commit the victim/affected party to future legal action.
Faculty membe rs are considered “responsible employees”at Northeastern University, meaning they are
required to report all reports of and information about alleged Prohibited Offenses to the Office for University
Equity and Compliance.
If you or someone you know has experienced a Prohibited Offense, confidential support and guidance can be
found through (https://www.northeastern.edu/ouec/resources/main-campus-resources/), University Health
and Counseling Services (UHCS) staff (http://www.northeastern.edu/uhcs/) and the Center for Spiritual
Dialogue and Service (CSDS) clergy members (http://www.northeastern.edu/spirituallife/). Employees within
the VRC, UHCS, and CSDS are not required to report allegations of Prohibited Offenses to the Officefor
University Equity and Compliance.
In case of an emergency, please call 911 OR NUPD’S Emergencyline: 617-373-3333.
Please visit www.northeastern.edu/titleix for a complete list of reporting options and resources, both on-and
off-campus.
Northeastern University Online Copyright Statement
Northeastern University Online is a registered trademark of Northeastern University. All other brand and
product names are trademarks or registered trademarks of their respective companies.
This course material is copyrighted and Northeastern University Online reserves all rights. No part of this
publication may be reproduced, transmitted, transcribed, stored in a retrieval system, or translated into any
language or computer language, in any form or by any means, electronic, mechanical, magnetic, optical,
chemical, manual, or otherwise, without the express prior written permission of Northeastern University Online.
Copyright 2021 © by Northeastern University Online
All Rights Reserved
The instructor reserves the right to amend this syllabus, both online and the document itself, during the term
and will notify students of the change(s). The revised syllabus is the official record of class policies and schedule
of due dates.
学霸联盟
Updated 3.2.21
Course Syllabus
Course Information
Course Number CED 6983
Course Name Business Fluctuations and Economic Forecasting
CRN 23597
Quarter / Year
Term Length 6 Weeks
Start / End Dates Mar 01, 2021 - Apr 10, 2021
Credit Hours 3.0
Course Format Virtual
Location
Instructor Information
Full Name: Mikhail Oet, PhD
NEU Email Address: m.oet@northeastern.edu
Office Hours: Email me to schedule an appointment
Second Point of Contact
In the event that some concern about the course arises and is not addressed by the instructor, please
contact:
Full Name: Fiona Creed, PhD, Acting Facuty Director, Global and Social Enterprise Domain
NEU Email Address: f.creed@northeastern.edu
If for any reason you wish to express a concern about anything that may impact your success in a course,
first speak directly with your Instructor. If you need additional support, please contact your Academic
Advisor.
Course Delivery
This course will be delivered using the virtual learning modality and I will be teaching remotely.I will
schedule weekly meetings using a video platform, usually Zoom or Teams, for students who would like to
join me synchronously. There is no requirement to participate synchronously, but at least asynchronous
participation and engagement is required. Students joining synchronously will be able to ask questions,
discuss, and interact with me and other students in real time. I will also be available for virtual office
hours on request by email.
Technical Requirements
Courses are available on Northeastern University’s Canvas at the following link:
http://canvas.northeastern.edu. Canvas Technical support and resources including 24/7 phone (1-833-450-
3937), and chat can be found on the help icon in Canvas. Northeastern Technical support can be accessed at
617-373-4357 (xHELP) or help@northeastern.edu.
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Each student is responsible for their access to the internet for purposes of this course and for research. Internet
access is a required component of this course and will not be accepted as an excuse for missed work. If you
know that you will be traveling, then make sure you plan accordingly.
Note regarding e-mail/voicemail: If you e-mail, please include your name and class title. Please allow up to 48
hours for an email reply. If you leave a voicemail, please remember to include your name, class title, and phone
number.
Course Prerequisites
• none
Course Description
This course provides students with the latest developments and forecasting methods in the analytics of
business fluctuations. The course emphasizes R language as means of economic data analysis and
provide students hands-on opportunities to deepen their understanding of methods of forecasting of
macroeconomic activity. Students are guided through the experiential case studies on macrofinancial
fluctuations from single equation to simultaneous equations systems (exponential smoothing,
forecasting with ARIMA models, Principal Component/Factor Analysis, Random forest analysis, trend /
cycle decomposition, FAVAR, global modelling).
Course Materials
Course Text(s)/Software/Tools
• Students are required to access Northeastern Canvas at http://canvas.northeastern.edu
Required Text
1. (H), R.J. Hyndman, G. Athanasopoulos, Forecasting Principles and Practice, available online
https://www.otexts.org/fpp3
2. (HW), J.E. Hanke, D.W. Wichern. (2009). Business Forecasting, 9th Edition, Pearson
(Ordering information: 1. Pearson, 2. Amazon, 3. NEU Bookstore)
3. (K), E. Kacapyr, Economic Forecasting, the state of the art, 1996 (Ordering information: 1.
Routledge, 2. Amazon, 3. NEU Bookstore)
4. (T), L. Tvede. Business Cycles: History, Theory and Investment Reality, 3rd Edition (Wiley),
2006 (Ordering information: 1. Wiley, 2. Amazon, 3. NEU Bookstore)
• Additional reading materials will be provided by instructor on Canvas.
Laboratory Materials:
5. https://www.datacamp.com/courses/free-introduction-to-r
6. HarvardX: PH125.1x, Data Science: R Basics, https://courses.edx.org/courses/course-
v1:HarvardX+PH125.1x+1T2018/course/
7. IMF Macroeconomic Forecasting, Archived class, https://www.edx.org/course/macroeconometric-
forecasting-imfx-mfx-0
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Recommended Texts
• Sanz, I. P. (2019). Machine Learning with R Quick Start Guide: A beginner's guide to
implementing machine learning techniques from scratch using R 3.5. Packt Publishing Ltd.
• A. Garratt et al., Global and National Macroeconometric Modelling: A Long-Run Structural
Approach, 2006
• Bomhoff, E. J. (1994). Financial forecasting for business and economics. Academic Press.
• A.A. Beaujean, Latent Variable Modeling Using R, 2014
• W.H. Finch, Jr. and B.F. French, Latent Variable Modeling with R, 2015
Required Software
• R software
Recommended Software
o EViews, http://register1.eviews.com/Lite/
Tools
This course contains audio-visual material, and, in some instances, you may be asked to participate in
audio-based activities, such as a Voice Discussion Board. A headset (headphones plus microphone) will
allow you to hear and record audio. The Logitech ClearChat Comfort USB Headset, or the Plantronics
Audio 470 or 500, or comparable brands/models, are recommended. Headsets can be purchased from
online vendors such as amazon.com, bestbuy.com, or newegg.com. This course may also require a
webcam. If your computer does not have an integrated webcam, webcams can be purchased at online
vendors such as amazon.com.
Program Learning Outcomes (PLOs)
Financial & Economic
Analysis/Data Analytics
Economics Knowledge
Base
Entrepreneurship/Intellec
tual Agility
Communication/Global
PLO 1 PLO 2 PLO 3 PLO 4
Use conceptual and
mathematical tools to
estimate economic
relationships such as
fluctuations in
employment, prices, and
economic growth.
Develop a coherent
framework for analyzing
the determination of
microeconomic and
macroeconomic variables
based on related theories
and models.
Design and implement a
project that applies
economic theories to
business and public policy
issues.
Develop a formal
proposal, real or
hypothetical, addressing a
global intercultural
communication challenge
in the field of commerce
and economic
development that has not
been adequately
addressed.
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SAIL Baseline Mapping
Enter 5 for Central, 4 for Significant, 3 for Moderate, 2 for Minimal, 1 for Potential, or 0
for None
Enter 1 for Passive
Engagement, 2 for Active
Engagement, or 3 for
Generative Engagement
Social
Consciousness
& Commitment
Global
Mindset Intellectual Agility
Personal &
Professional
Effectiveness
Well-
Being Level of Engagement
4 4 4 4 3 3
Course Learning Outcomes
Based on satisfactory completion of this course, by the end of the class students will be able to:
CLO1: History of modern business fluctuations
CLO2: Business cycle theories
CLO3: Business fluctuations and asset prices
CLO4: Exploring and visualizing time series
CLO5: Forecasting with exponential smoothing
CLO6: Forecasting with ARIMA models
CLO7: Advanced methods of forecasting
CLO8: Dimensionality reduction, Principal component, and Factor analysis
CLO9: Identification of critical episodes
CLO10: Tree-based methods and Random Forest.Assess the impact of macro-shocks on capital markets
with correlation analytics
Expectations
• Workload
o Students should expect 3 hours per week of classroom-related discussion and asynchronous
weekly learning plus a minimum of 9 hours per week of out-of-class student work for this 6-
week course.
o APA citations
Attendance Policy
Students are required to attend all scheduled classroom sessions virtually (synchronously or
asynchronously). Students are required to engage with all posted material. Student engagement with
the classroom session material and the weekly posted material is tracked. Absence of engagement with
the classroom sessions and the weekly instructional materials results in loss of score allocated for the
weekly classroom activity.
Policy on late work
A deduction of 20% percent will be made for each day (counted as any portion of a 24-hour period)
that an assignment is late. Late submissions for assignments due by 11:59 PM EST Thursday will not be
accepted after 5 PM EST Friday. Otherwise, work will no longer be accepted 3 days after the specified
deadline, unless specific arrangements have been made with the instructor. With prior permission
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only, any request for an exception to the late submission policy needs be supported by with a signed
doctor’s note. If an extension is granted, all missing assignments are expected to be submitted within 1
week of the termination of the period covered by the doctor’s note.
Policy on early submissions
Early submissions are encouraged. Draft materials received at least 24 hours before the deadline (the
in-advance-submission) will receive feedback and suggestions, allowing for improved final submission
before the deadline. Only the last submission received before the deadline will be graded.
Course Methodology
Each week, you will be expected to:
• Review the week's learning objectives
• Complete all assigned readings
• For each Reading Text Chapter assigned, create a PowerPoint slide summarizing the reading and
submit by email by due date (generally two days before next class) a minimum of one slide (per
chapter).
• Complete all lecture materials for the week: View all assigned videos and/or PowerPoint slides
(synchronously or asynchronously).
• Participate in the ongoing Discussion Board/Google document activities.
• Complete and submit all assignments and project by the due dates.
• Modelling and laboratory assignments: as assigned.
Participation/Class Discussion Board/Team Google document/Shared Google drive
Note: the schedule below is a typical schedule but may be modified to accommodate increased or
decreased assignment load during a specific week. Please consult instructions in the weekly
“Assignment” section on Canvas.
Participation on the Class Discussion Board/Team Google document/Shared Google drive is an integral
part of any online learning community. Each week students must post at least one primary response
(answering a discussion question posted by the instructor) and two secondary responses (responses to
other students’ posts). Participation in Discussion Board/Team Google document is worth 10% of the
total course grade. All postings are expected to be professional in tone, clear, comprehensible,
competently produced and delivered, and their content should reflect an understanding of at least the
lectures and readings assigned. All responses are required to be substantive and related to the weekly
topic(s) under discussion. They will be evaluated solely based on clarity and originality of posts, as well
as the degree to which peers' learning is enriched by those comments and posts. Posts will not be
evaluated based on frequency or length. In other words, quality of the posts is more important than
quantity of posts.
The Class Discussion Board and the Team Google document are spaces for academic exchanges. As a
result, you must check for proper and exacting punctuation, spelling, and grammar. In addition, you
must reference all outside sources in correct citation format. It is crucial that all participants maintain a
high regard for proper decorum in the Class Discussion Board/Team Google Document. A grading rubric
for Discussion Board/Team Google document responses is provided.
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Please treat your classmates and the instructors with the utmost respect. Inappropriate posts will be
removed immediately. The instructor reserves the right to penalize students for repeated violations of
the participation policy within a course.
In the Class Discussion board/Team Google document and in class, high quality contributions advance
the class discussions and do not simply summarize the material that was assigned. Quality
contributions consider not only the instructor’s questions but also your classmates’ contributions.
Communication/Submission of Work
Submissions shall be made through one of three possible means, as specified in a particular assignment:
1. Class Discussions submissions need to be made in the relevant location in Canvas.
2. Data, all analysis, and models used in the project need to be uploaded to the relevant Team
subfolder in a shared Google drive
3. Team Google document needs to be shared in the respective team folder of the shared Google
drive.
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Updated 3.2.21
Evaluation Standards
GRADING RUBRIC: Discussion Board /Team Google document Participation
Weight Criteria
EXCEEDING
STANDARDS
100%
MEETING
STANDARDS
80%
APPROACHING
STANDARDS
50%
BELOW
STANDARD
25%
25% Comprehension
Explains key concepts in
one's own words and
illustrates understanding
of material via unique
examples and personal
perspective.
Explains key concepts in
one's own words and
illustrates understanding
of material by citing
examples.
Able to explain key
concepts in one's own
words.
Unable to put key
concepts in one's own
words.
25% Engagement
Adds substantive
information, asks
meaningful questions to
peers, and provides
substantive responses.
Adds substantive
information to the
discussion and asks
meaningful questions to
peers.
Adds substantive
information to the
discussion.
Does not add substantive
information to the
discussion.
25% Connections
Integrates learned
concepts by making
strong connections to
personal experience or
previous understanding.
Integrates learned
concepts by making
explicit connections to
personal experience or
previous understanding.
Integrates learned
concepts by making
implicit connections to
personal experience or
previous understanding.
Does not integrate
learned concepts by
making connections to
personal experience or
previous understanding.
25% Writing
Writes clearly and
concisely with no errors
related to organization,
grammar, style, and
citations.
Writes clearly and
concisely with some
errors related to
organization, grammar,
style, and citations.
Writes clearly with very
few errors related to
organization, grammar,
style, and citations.
Does not write clearly
with many errors related
to organization, grammar,
style, and citations.
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Updated 3.2.21
GRADING RUBRIC: Written Communication
Criteria Exceeding Standards Meeting Standards Approaching Standards Below Standards
CONTEXT 100% 80% 50% 25%
Weight 20%
Demonstrates a thorough
understanding of context,
audience, and purpose that
is responsive to the
assigned task(s) and
focuses all elements of the
work.
Demonstrates adequate
consideration of context,
audience, and purpose
and a clear focus on the
assigned task(s) (e.g., the
task aligns with audience,
purpose, and context).
Demonstrates awareness
of context, audience,
purpose, and to the
assigned tasks(s) (e.g.,
begins to show awareness
of audience's perceptions
and assumptions).
Demonstrates minimal
attention to context,
audience, purpose, and to
the assigned tasks(s) (e.g.,
expectation of instructor
or self as audience).
CONTENT 100% 80% 50% 25%
Weight 20%
Uses appropriate, relevant,
and compelling content to
illustrate mastery of the
subject, conveying the
writer's understanding, and
shaping the whole work.
Uses appropriate,
relevant, and compelling
content to explore ideas
within the context of the
discipline and shape the
whole work.
Uses appropriate and
relevant content to
develop and explore ideas
through most of the work.
Uses appropriate and
relevant content to
develop simple ideas in
some parts of the work.
CONVENTIONS 100% 80% 50% 25%
Weight 20%
Demonstrates detailed
attention to and successful
execution of a wide range
of conventions particular to
a specific discipline and/or
writing task (s) including
defining terms,
organization, content,
presentation, formatting,
and stylistic choices
Demonstrates consistent
use of important
conventions particular to
a specific discipline
and/or writing task(s),
including defining terms,
organization, content,
presentation, and stylistic
choices
Follows expectations
appropriate to a specific
discipline and/or writing
task(s) for basic
organization, content, and
presentation.
Attempts to use a
consistent system for
basic organization and
presentation.
SOURCES 100% 80% 50% 25%
Weight 20%
Demonstrates skillful use of
high- quality, credible,
relevant sources to develop
ideas that are appropriate
for the discipline and genre
of the writing
Demonstrates consistent
use of credible, relevant
sources to support ideas
that are situated within
the discipline and genre
of the writing.
Demonstrates an attempt
to use credible and/or
relevant sources to
support ideas that are
appropriate for the
discipline and genre of
the writing.
Demonstrates an attempt
to use sources to support
ideas in the writing.
MECHANICS 100% 80% 50% 25%
Weight 20%
Uses graceful language that
skillfully communicates
meaning to readers with
clarity and fluency and is
virtually error free.
Uses straightforward
language that generally
conveys meaning to
readers. The language in
the portfolio has few
errors.
Uses language that
generally conveys
meaning to readers with
clarity, although writing
may include some errors.
Uses language that
sometimes impedes
meaning because of
errors in usage.
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Grading
Graduate Programs Final Grading Scale
95-100% A 87-89.9% B+ 77-79.9% C+ 69.9% or below F 84-86.9% B 74-76.9% C
90-94.9% A- 80-83.9% B- 70-73.9% C-
Grade Breakdown
Title Description Grade (Pts or %)
1 Discussions 10%
2 Homeworks 50%
5 Final Project 40%
Total 100%
Course Schedule
Week Topic Reading Assignments CLO SLO
1 Discovery of
business
cycles
• Money as wealth: John Law and Banque
Royal
• Money supply: France 1719-1720
• The birth of central banking: Quesnay,
Cantillon, Smith, Thorton, Say, Ricardo, Mill
• Pioneers of business cycle studies: Babbage,
Juglar, Walras, Pareto, Jevons, Newcomb,
Edgeworth
• Classical levers of business cycles: asset
prices and psychology (Marshall, Pigou),
capacity building (Hobson, Tugan-
Baranovsky, Catchings and Foster, Clark),
technological innovation (Spiethoff), interest
rates (Wicksell, Kassel, Roberston, Hawtrey)
• Classical empirical studies of business cycles:
Mitchell, Burns, Kitchin, Kuznets, Kondratieff
• The emergence business cycle forecasting:
Fisher, Babson.
• Policy responses: Keynes, Hayek
• Reading 1: (T) Ch. 1 , 2, 3, 4, 6, 7, 8, 9, 10
• Problem Sets: Complete and submit homework 1:
o Create and post 1 slide for each chapter in Reading
1
• Discussion Board Activity:
o Review: instructor and classmate slides for reading
1
o Post answers to instructor’s question(s) by
Thursday and questions/ comments in response to
your peers’ postings by Sunday
• Classroom Activity
CLO 1
CLO 2
SLO 1
SLO 2
2 First business
cycle theories:
the observed
and the
unobservable
• Entrepreneurship’s role in business
fluctuations: Shumpeter
• Inherent financial instability: Minsky,
Kuznets, Friedman
• Mathematical dynamics and econometric
forecasting: Tinbergen, Frisch, Cobwebb
theorem, multiplier, accelerator, lags,
feedbacks
• Neoclassical synthesis and general
equilibrium: Arrow, Debreu
• Real business cycle theories: Kydland,
Prescott
• Macroeconometric Models: Klein
• Inventory cycles: Metzler
• Fat tails: Hurst, Mandelbrot
• Complexity and chaos: May, Lorenz,
Feigenbaum
• Modeling paradigms: econometrics, system
dynamics, artificial intelligence
• Reading 2: (T) Ch. 11, 12, 13, 14, 15, 16, 17
• Problem Sets: Complete and submit homework 2:
o Create and post 1 slide for each chapter in Reading
2
• Discussion Board Activity:
o Review: instructor and classmate slides for reading
2
o Post answers to instructor’s question(s) by
Thursday and questions/ comments in response to
your peers’ postings by Sunday
• Classroom Activity
CLO 3
CLO 4
SLO 2
SLO 3
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Updated 3.2.21
3 Introduction
to R
• Presentation of advanced correlation maps
visualising interconnectivity of markets
• Focus on Value at Risk analytics and outlier
detection
• Development of early warning signals
through monitoring of interconnected
market dynamics and visual
• Statistical identification of hidden patterns
in complex data
• Hands-on use of dashboards for Case Studies
(e.g. US Housing Bubble and Crisis)
• Review Laboratory materials (5) Intro, Sections 1, 2 , 3, 4,
exercise slides/screenshots/text)
• Problem Sets: Complete and submit Homework 3
(Laboratory assignment 1)
• Problem Sets: Complete and submit Homework 4
(Laboratory assignment 2)
• Discussion Board Activity: Post answers to instructor’s
question(s) by Thursday and questions/ comments in
response to your peers’ postings by Sunday
o Discussion questions:
https://www.datacamp.com/courses/free-
introduction-to-r
• Classroom Activity
CLO 1
CLO 2
CLO 3
CLO 4
SLO 3
SLO 4
SLO 5
4 Stress Testing
Correlation
Networks
• Focus on financial markets as a complex
system with numerous measurable
interdependencies
• Production of 'what if' scenarios to predict
movements of markets under stress
• Stress testing correlation structures
• Hands-on use of interactive dashboards in
relation to Case Studies (e.g. Brexit
Referendum and US Presidential Election)
• Reading 1: Economic Forecasting
(K) Ch. 1, 2;`
(H) Ch. 2, 3.
• Reading 2: (K) Ch. 3, 4;
(H) Ch. 7.
• Reading 3: (K) Ch. 5, 6;
(H) Ch. 8.
• Reading 4: (K) Ch. 7, 8;
(H) Ch. 9, 11.
• Problem Sets: Complete and submit homework 4:
o 1 slide ea. for Chapter in Reading 1, Lab Assignment
3 (DataCamp for Classroom, Forecasting in R, Unit
1: Exploring and visualizing time series in R AND
Unit 2: Benchmark methods and forecast accuracy)
o 1 slide ea. for Chapter in Reading 2, Lab Assignment
4 (DataCamp for Classroom, Forecasting in R, Unit
3: Exponential smoothing)
o 1 slide ea. for Chapter in Reading 3, Lab Assignment
5 (DataCamp for Classroom, Forecasting in R, Unit
4: Forecasting with ARIMA models)
o 1 slide ea. for Chapter in Reading 4, Lab Assignment
6 (DataCamp for Classroom, Forecasting in R, Unit
5: Advanced methods)
• Discussion Board Activity:
o Review: slides for readings 1 and 2
o Post answers to instructor’s question(s) by
Thursday and questions/ comments in response to
your peers’ postings by Sunday
• Classroom Activity
CLO 2
CLO 6
CLO 7
SLO 3
SLO 4
SLO 5
5 Applications
of
quantitative
social science
research
methods
• Exploratory methods
o Principal Component and Factor
Analysis
o Latent variables with R
o QCA
o Network analysis
• XN Project activity unit 1
• XN Project activity unit 2
• XN Project activity unit 3
• XN Project activity unit 4
• Problem Sets: Complete and submit homework 4:
o Lab assignment: Complete course record in
https://campus.datacamp.com/courses/machine-
learning-with-tree-based-models-in-r
• Discussion Board Activity:
o Review: slides for XN Project activity units 1, 2, 3, 4
o Post answers to instructor’s question(s) by
Thursday and questions/ comments in response to
your peers’ postings by Sunday
• Classroom Activity
CLO 5 SLO 3
SLO 4
SLO 5
6 Applications
of early
warning
methods
• Confirmatory methods
o Tree-based Methods
o Random Forest
o Early warning systems
o Global modelling
• XN Project activity unit 5
• XN Project activity unit 6
• XN Project activity unit 7
• XN Project activity unit 8
• Discussion Board Activity:
CLO 5
CLO 6
CLO 7
SLO 3
SLO 4
SLO 5
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o Review: slides for XN Project activity units 5, 6, 7, 8
o Post answers to instructor’s question(s) by
Thursday and questions/ comments in response to
your peers’ postings by Sunday
• Classroom Activity
End-of-Course Evaluation Surveys
Your feedback regarding your educational experience in this class is very important to the College of
Professional Studies. Your comments will make a difference in the future planning and presentation of our
curriculum.
At the end of this course, please take the time to complete the evaluation survey at
https://neu.evaluationkit.com. Your survey responses are completely anonymous and confidential. For
courses 6 weeks in length or shorter, surveys will be open one week prior to the end of the courses; for courses
greater than 6 weeks in length, surveys will be open for two weeks. An email will be sent to your HuskyMail
account notifying you when surveys are available.
Academic Integrity
A commitment to the principles of academic integrity is essential to the mission of Northeastern University. The
promotion of independent and original scholarship ensures that students derive the most from their educational
experience and their pursuit of knowledge. Academic dishonesty violates the most fundamental values of an
intellectual community and undermines the achievements of the entire University.
As members of the academic community, students must become familiar with their rights and responsibilities. In
each course, they are responsible for knowing the requirements and restrictions regarding research and writing,
examinations of whatever kind, collaborative work, the use of study aids, the appropriateness of assistance, and
other issues. Students are responsible for learning the conventions of documentation and acknowledgment of
sources in their fields. Northeastern University expects students to complete all examinations, tests, papers,
creative projects, and assignments of any kind according to the highest ethical standards, as set forth either
explicitly or implicitly in this Code or by the direction of instructors.
Go to http://www.northeastern.edu/osccr/academic-integrity-policy/ to access the full academic integrity
policy.
CPS expects independent and original work. Dishonesty and/or carelessness violates fundamental values of an
intellectual and professional community and will be reported to the Office of Student Conduct and Conflict
Resolution (OSCCR) as a violation of the Academic Integrity Policy. To safeguard the integrity of assignments and
programs, your course may use systems such as TurnItIn, which checks written work, and Examity, an online
exam proctoring system. Work that contains academic integrity violations (AIV) will be graded on a case by case
basis. Work displaying AIV may earn a failing grade, a zero, or even result in the instructor assigning the student
a failing grade for the class. Students may not withdraw from a class to avoid the grade penalty for serious
academic integrity violations.
For additional information or for answers to frequently asked questions, please visit:
https://cps.northeastern.edu/academic-resources/academic-integrity
You may also email CPS-AcademicIntegrity@northeastern.edu.
Student Accommodations
The College of Professional Studies is committed to providing equitable access to learning opportunities to
students with documented disabilities (e.g. mental health, attentional, learning, chronic health, sensory, or
Page | 12
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physical). To ensure access to this class, and program, please contact The Disability Resource Center
(http://www.northeastern.edu/drc/) to engage in a confidential conversation about the process for requesting
reasonable accommodations in the classroom and clinical or lab settings. Accommodations are not provided
retroactively so students are encouraged to register with the Disability Resource Center (DRC) as soon as they
begin their program. The College of Professional Studies encourages students to access all resources available
through the DRC for consistent support.
Library Services
The Northeastern University Library is at the hub of campus intellectual life. Resources include over 900,000
print volumes, 206,500 e-books, and 70,225 electronic journals.
For more information, visit http://library.northeastern.edu/.
Wyzant Tutoring Services
Northeastern University's College of Professional Studies is covering the cost of 4 hours of tutoring from Wyzant
to help ensure your success in challenging courses. Tutors on Wyzant have helped thousands of students in 300+
subjects ranging from College Algebra to Academic Writing, Statistical Analysis to Microbiology.Click here to
access your free tutoring through Northeastern University's Wyzant account.
Access your free tutoring using your Northeastern login credentials. Indicate your program, time zone, the
course you'd like support in, and the specific topics or materials you'd like help with.
You'll receive an activation email from Wyzant for Higher Ed. (If you don't see it, check your spam or junk
folders.) From the email, click on the activation button.
Potential tutors will begin reaching out to you. Their messages will be sent to your Northeastern email inbox and
will be accessible via your Wyzant account dashboard.
Respond back to the tutors you believe might be a good fit to schedule an online session when it's convenient
for you — even late at night!
24/7 Canvas Technical Help
For immediate technical support for Canvas, call 1-833-450-3937. You can chat and report an issue to Canvas
technical support right from within Canvas through the Help icon located in the Canvas global navigation.
myNortheastern, e-mail, and basic technical support
Visit the Information Technology Services (ITS) Support Portal
Email: help@northeastern.edu
ITS Customer Service Desk: 617-373-4357 (help)
Catalog
The College of Professional Studies Graduate Catalog is a reference/resource with information about curricula,
resources, and academic and student policies.
For more information, visit http://www.cps.neu.edu/student-resources/.
Diversity and Inclusion
Northeastern University and the and the Office of Institutional Diversity and Inclusion (OIDI) is committed to
equal opportunity, affirmative action, diversity and social justice while building a climate of inclusion on and
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beyond campus. In the classroom, member of the University community work to cultivate an inclusive
environment that denounces discrimination through innovation, collaboration and an awareness of global
perspectives on social justice.
Please visit http://www.northeastern.edu/oidi/ for complete information on Diversity and Inclusion
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TITLE IX
Title IX of the Education Amendments of 1972 protects individuals from sex or gender-based
discrimination, including discrimination based on gender-identity, in educational programs and activities that
receive federal financial assistance.
Northeastern’s Title IX Policy prohibits sex and gender-based discrimination, including sexual harassment,
sexual assault, sexual exploitation, relationship or domestic violence, and stalking. The Title IX Policy refers to
sex and gender-based discrimination as “Prohibited Offenses.” The Title IX Policy applies to the entire
Northeastern community, including students, faculty and staff of all gender identities.
Allegations of Prohibited Offenses can be reported to the Title IX Coordinator within The Office for University
Equity and Compliance at: titleix@northeastern.edu and/or through the Northeastern University Police
Department (NUPD) by phone: for an Emergency 617.373.3333; for Non-Emergency 617.373.2121. Reporting
to NUPD does NOT commit the victim/affected party to future legal action.
Faculty membe rs are considered “responsible employees”at Northeastern University, meaning they are
required to report all reports of and information about alleged Prohibited Offenses to the Office for University
Equity and Compliance.
If you or someone you know has experienced a Prohibited Offense, confidential support and guidance can be
found through (https://www.northeastern.edu/ouec/resources/main-campus-resources/), University Health
and Counseling Services (UHCS) staff (http://www.northeastern.edu/uhcs/) and the Center for Spiritual
Dialogue and Service (CSDS) clergy members (http://www.northeastern.edu/spirituallife/). Employees within
the VRC, UHCS, and CSDS are not required to report allegations of Prohibited Offenses to the Officefor
University Equity and Compliance.
In case of an emergency, please call 911 OR NUPD’S Emergencyline: 617-373-3333.
Please visit www.northeastern.edu/titleix for a complete list of reporting options and resources, both on-and
off-campus.
Northeastern University Online Copyright Statement
Northeastern University Online is a registered trademark of Northeastern University. All other brand and
product names are trademarks or registered trademarks of their respective companies.
This course material is copyrighted and Northeastern University Online reserves all rights. No part of this
publication may be reproduced, transmitted, transcribed, stored in a retrieval system, or translated into any
language or computer language, in any form or by any means, electronic, mechanical, magnetic, optical,
chemical, manual, or otherwise, without the express prior written permission of Northeastern University Online.
Copyright 2021 © by Northeastern University Online
All Rights Reserved
The instructor reserves the right to amend this syllabus, both online and the document itself, during the term
and will notify students of the change(s). The revised syllabus is the official record of class policies and schedule
of due dates.
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