Course Syllabus – OPRE 6359 Spring 2019/1
OPRE 6359.501
Statistics for Data Sciences
Term: Spring 2019
Professor: Monica E. Brussolo, Ph.D.
Time: Thursdays 7 – 9:45 pm
Location JSOM 1.217
CONTACT INFORMATION:
Office Phone 972-883-4411
Office Location JSOM 3.231
Email Address [email protected]
Office Hours By appointment on Tuesday or Friday 10 am-12 pm.
Use this link: http://utdscm.genbook.com and select Course Office Hours.
Other Information Please ensure e-mail messages include your class in the subject line or in your signature.
Email is the most effective way to reach me.
TA Information Zihao Qu / Office hours Wednesday 1-3 pm / Office 14.211
[email protected]
GENERAL COURSE INFORMATION
Pre-requisite
OPRE 6301.
Computer requirement:
You need access to a laptop, as we will be using R/Stata during the class and for homeworks and final
project.
Course description
代写OPRE 6359作业
This course uses statistical methods to analyze data from observational studies and experimental designs
to communicate results to a business audience. The course mandates prior knowledge of fundamental
statistical concepts such as measures of central location, standard deviations, histograms, the normal and
t-distributions (knowledge of calculus is not required). The course also emphasizes interpretation and
inference, as well as computation using a statistical software package such as R or STATA.
Learning outcomes and expectations
Active and informed participation is expected from every student. Class sessions will consist primarily
of lecture, with some discussions and in-class exercises as appropriate to the topic being covered.
Students are expected to read the appropriate assigned readings in preparation for class and exams.
Students should expect to spend an average of 9 to 12 hours per week on class preparation and studying
activities outside of class meetings.
This course involves a lot of computation, and there is no substitute for getting your hands dirty. I
expect to make my share of mistakes this semester (some intentional, some not), and we will learn
from them together. In data analysis, you learn as much when things “don’t work” than when they go
as planned. This is not an R or Stata course, but a Statistics course in which we will use those packages
as tools to achieve our objectives.
Learning outcomes – upon completion of this course, students will be able to accomplish the following:
1. Develop and test hypotheses using multiple statistical methods.
2. Understand differences between observational and experimental studies.
3. Learn how randomization and sampling influence scope of inference.
4. Explore experimental and observational designs that compare multiple populations when the
response is continuous or binary.
5. Communicate the findings of a statistical analysis from these new methods in a clear, concise,
and scientific manner.
6. Integrate and analyze real-world datasets using common software packages.
Course Syllabus – OPRE 6359 Spring 2019/2
Required text
Ramsey, F. L., and Schafer, D. W. (2013), The Statistical Sleuth: A Course in Methods of Data
Analysis (3rd ed.), Boston, MA: Brooks/Cole,
Required software and downloads
R & R-studio
Stata
Book files: www.statisticalsleuth.com.
This link has a package in R with all the files (Sleuth3) http://r-forge.r-project.org/R/?group_id=585
COURSE GRADING INFORMATION
Exams/Homeworks
i Two (2) exams in the classroom. They contribute 30% toward your final course grade each (60%).
ii Four (4) homeworks, posted a week in advance on eLearning and due by midnight on the due date, they
contribute 15% of your final grade. No late deliveries are accepted. You are allowed to work with
your classmates on these homeworks but is it expected that each student will write and prepare his/her
own solution so if you are asked to explain any of your answers; you are capable to do so.
iii Final research project. You will select one (or more) techniques that we discussed in class to prepare
a research project. The final research project will include finding a problem of your interest, setting
up the research hypotheses, finding the data, performing the analysis and writing the final paper. You
will deliver your final paper and a one-page summary of your paper. The summary will be delivered
in advance to the class as that we will discuss the last day of class. This will contribute 25% of your
grade. A paper rubric and a list of suggested sites to find real datasets will be posted on week 3.
Make-up exams may be offered under justified unavoidable circumstances (sickness, death of a close
relative). Please consult with the instructor. Students who do not show up for an exam, and for whom
alternate arrangements for a make-up exam have not been discussed with the Instructor prior to the date
of the exam, will receive a score of zero for that exam. No exceptions.
In all your deliverables, and the exams, evidence of copying or cheating will be penalized as defined in
the Academic Dishonesty section of this syllabus.
Additional information
Extra credit will NOT be offered for any graded portions of this course.
Summary of course grading
Graded Component % Contribution
Exam 1 30%
Exam 2 30%
Homeworks 15%
Final research project 25%
Course Total: 100%
Grading criteria
Letter Grade A A- B+ B B- C+ C F
Percentage 93% 90% 87% 83% 80% 75% 70% Below 70%
Important Note about Grades: If any adjustments to final grades are necessary, they will be determined
based on the performance of the class. Unless there is an error in grading the final exam, letter grades are
FINAL.
Course Syllabus – OPRE 6359 Spring 2019/3
CLASSROOM PARTICIPATION
PowerPoint slides and lecture notes are utilized by the Instructor to lead and enhance the in-class
lecture. To encourage critical thinking, students are expected to attend class and take notes. Being
proactive in the classroom by asking questions is encouraged. Students are expected to read the
appropriate textbook sections prior to coming to class.
TENTATIVE COURSE SCHEDULE
The following is a tentative schedule which will be followed as closely as possible. However, should
changes become necessary, they will be announced in class. It is your responsibility to keep track of
announcements regarding changes to this schedule.
WEEK # DATE LECTURE TOPICS/EXAMS
Week 1 Jan 17 Chapter 1: Drawing Statistical Conclusions
Chapter 23: Elements of Research Design
Week 2 Jan 24 Chapter 2: Inference Using t-Distributions
Chapter 3: Data Screening, Assumptions, and Transformations
Week 3 Jan 31 Chapter 4: Alternatives to the t-Tools for One, Two, and Multiple Samples
Week 4 Feb 7 Chapter 5: Comparisons among Several Samples
Week 5 Feb 14 Chapter 6: Linear Combinations and Multiple Comparison Problem
Week 6 Feb 21 Chapter 8: Evaluating the Assumptions of Simple Linear Regression
Week 7 Feb 28 Exam 1– in the classroom
Includes: Chapters 1-6, 8, 23
Week 8 March 7 Chapter 10: Inferential tools for Multiple Regression
Week 9 March 14 Chapter 12: Strategies for Variable Selection
Section 9.3: Specially Constructed Explanatory Variables
Week 10 March 21 Spring Break – no class this week
Week 11 March 28 Chapter 13: The Analysis of Variance for Two-Way Classification
Week 12 April 4 Chapter 16: Repeated Measures and other Multivariate Responses
Section 17.3: Principal Components
Week 13 April 11 Chapter 18: Comparison of Proportions or Odds
Section 19.3: The Chi-Squared Test for Goodness of Fit
Week 14 April 18 Chapter 20: Logistic Regression for Binary Response Variables
Week 15 April 25
Exam 2 – in the classroom
Includes: Chapters 10,12,13,16, 18, 20
Sections 9.3, 17.3 and 19.3
Week 16 May 2 Final paper delivery and discussion/presentation in class.
* On Exam day: A cheat-sheet one page, written one side, which will be turned in with your exam. Bring a
calculator that has at least these minimum capabilities: basic 4-functions, square root, exponent and it is able to
display at minimum 4 decimal places. Exams will not require the use of your computer.
MOBILE PHONES AND COMPUTERS
No use of mobile phones for talking or texting is allowed in the classroom. If you must make a call during
class or breaks, please step outside of the classroom.
Taking unauthorized pictures or video within the classroom, with your mobile phone or a camera, is an
infringement of privacy rights and it is prohibited.
Course Syllabus – OPRE 6359 Spring 2019/4
Computers may be brought to class and be used for the purpose of following along during computer
software demonstration portions of class lecture. Surfing the internet during lecture is a distraction to
other students and the Instructor and interferes with learning. These distractions will be regarded as an
infringement upon the rights of others to learn within the classroom, and students are subject to referral
to the appropriate Dean.
Special Assistance
For help you succeed in the class, the following resources are available:
Your instructor, the teaching assistant assigned to this class, the Student Counseling Center (SSB
4.600) among other resources.
Accessibility Accommodations
It is the policy and practice of The University of Texas at Dallas to make reasonable accommodations for
students with properly documented disabilities. However, written notification from the Office of Student
AccessAbility (OSA) is required. If you are eligible to receive an accommodation and would like to
request it for this course, please discuss it with me and allow one week advance notice. Students who
have questions about receiving accommodations, or those who have, or think they may have, a disability
(mobility, sensory, health, psychological, learning, etc.) are invited to contact the Office of Student
AccessAbility for a confidential discussion. OSA is located in the Student Services Building, suite 3.200.
They can be reached by phone at (972) 883-2098, or by email at [email protected].
Academic Integrity
The faculty and administration of the School of Management expect from our students a high level of
responsibility and academic honesty. Because the value of an academic degree depends upon the absolute
integrity of the work done by the student for that degree, it is imperative that a student demonstrate a high
standard of individual honor in his or her scholastic work. We want to establish a reputation for the
honorable behavior of our graduates, which extends throughout their careers. Both your individual
reputation and the school’s reputation matter to your success.
The Judicial Affairs website lists examples of academic dishonesty. Dishonesty includes, but is not limited
to cheating, plagiarism, collusion, facilitating academic dishonesty, fabrication, failure to contribute to a
collaborative project and sabotage. Some of the ways students may engage in academic dishonesty are:
Coughing and/or using visual or auditory signals in a test;
Concealing notes on hands, caps, shoes, in pockets or the back of beverage bottle labels;
Writing in blue books prior to an examination;
Writing information on blackboards, desks, or keeping notes on the floor;
Obtaining copies of an exam in advance;
Passing information from an earlier class to a later class;
Leaving information in the bathroom;
Exchanging exams so that neighbors have identical test forms;
Having a substitute take a test and providing falsified identification for the substitute;
Changing a graded paper and requesting that it be regraded;
Failing to turn in a test or assignment and later suggesting the faculty member lost the item;
Stealing another student’s graded test and affixing one’s own name on it;
Recording two answers, one on the test form, one on the answer sheet;
Marking an answer sheet to enable another to see the answer;
Encircling two adjacent answers and claiming to have had the correct answer;
Stealing an exam for someone in another section or for placement in a test file;
Using an electronic device to store test information, or to send or receive answers for a test;
Consulting assignment solutions posted on websites of previous course offerings;
Transferring a computer file from one person’s account to another;
Transmitting posted answers for an exam to a student in a testing area via electronic device;
Course Syllabus – OPRE 6359 Spring 2019/5
Downloading text from the Internet or other sources without proper attribution;
Citing to false references or findings in research or other academic exercises;
Submitting a substantial portion of the same academic work more than once without written
authorization from the instructor.
http://www.utdallas.edu/judicialaffairs/UTDJudicialAffairs-Basicexamples.html
Plagiarism
Plagiarism on written assignments, especially from the web, from portions of papers for other classes, and
from any other source is unacceptable. On written assignments, this course will use the resources of
turnitin.com, which searches the web for plagiarized content and is over 90% effective.
Academic Dishonesty
Students in this course suspected of academic dishonesty are subject to disciplinary proceedings, and if
found responsible, the following minimum sanctions will be applied:
Homework – Zero for the Assignment
Case Write-ups – Zero for the Assignment
Quizzes – Zero for the Quiz
Presentations – Zero for the Assignment
Group Work – Zero for the Assignment for all group members
Exams – F for the course
These sanctions will be administered only after a student has been found officially responsible for academic
dishonesty, either through waiving their right for a disciplinary hearing, or being declared responsible after
a hearing administered by Judicial Affairs and the Dean of Student’s Office.
In the event that the student receives a failing grade for the course for academic dishonesty, the student is
not allowed to withdraw as a way of preventing the grade from being entered on their record. Where a
student receives an F in a course and chooses to take the course over to improve their grade, the original
grade of F remains on their transcript, but does not count towards calculation of their GPA.
The School of Management also reserves the right to review a student’s disciplinary record, on file with the
Dean of Students, as one of the criteria for determining a student’s eligibility for a scholarship.
Judicial Affairs Procedures
Under authority delegated by the Dean of Students, a faculty member who has reason to suspect that a
student has engaged in academic dishonesty may conduct a conference with the student in compliance with
the following procedures:
(i) the student will be informed that he/she is believed to have committed an act or acts of academic
dishonesty in violation of University rules;
(ii) the student will be presented with any information in the knowledge or possession of the
instructor which tends to support the allegation(s) of academic dishonesty;
(iii) the student will be given an opportunity to present information on his/her behalf;
(iv) after meeting with the student, the faculty member may choose not to refer the allegation if he/she
determines that the allegations are not supported by the evidence; or
(v) after meeting with the student, the faculty member may refer the allegations to the dean of
students along with a referral form and all supporting documentation of the alleged violation.
Under separate cover, the faculty member should forward the appropriate grade to be assessed if
a student is found to be responsible for academic dishonesty;
(vi) the faculty member may consult with the dean of students in determining the recommended grade;
(vii) the faculty member must not impose any independent sanctions upon the student in lieu of a
referral to Judicial Affairs;
(viii) the faculty member may not impose a sanction of suspension or expulsion, but may make this
recommendation in the referral documentation
If the faculty member chooses not to meet with the student and instead forwards the appropriate
documentation directly to the dean of students, they should attempt to inform the student of the allegation
Course Syllabus – OPRE 6359 Spring 2019/6
and notify the student that the information has been forwarded to the Office of Dean of Students for
investigation.
The student, pending a hearing, remains responsible for all academic exercises and syllabus requirements.
The student may remain in class if the student’s presence in the class does not interfere with the professor’s
ability to teach the class or the ability of other class members to learn. (See Section 49.07, page V-49-4 for
information regarding the removal of a student from class).
Upon receipt of the referral form, class syllabus, and the supporting material/documentation from the
faculty member, the dean shall proceed under the guidelines in the Handbook of Operating Procedures,
Chapter 49, Subchapter C. If the respondent disputes the facts upon which the allegations are based, a fair
and impartial disciplinary committee comprised of UTD faculty and students, shall hold a hearing and
determine the responsibility of the student. If they find the student in violation of the code of conduct, the
dean will then affirm the minimum sanction as provided in the syllabus, and share this information with the
student. The dean will review the student’s prior disciplinary record and assess additional sanctions where
appropriate to the circumstances. The dean will inform the student and the faculty member of their decision.
UT Dallas Syllabus Policies and Procedures
The information contained in the following link constitutes the University’s policies and procedures
segment of the course syllabus. Please go to http://go.utdallas.edu/syllabus-policies for these policies.
The descriptions and timelines contained in this syllabus are subject to change at the discretion of
the Professor.
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