Department of Accounting and Business Analytics MGTSC312
Probability and Statistics for Business Syllabus - Fall 2022
Section Class Time Location
Course A01 (30250) MWF 0800-0850 CCIS 1-430 Course A02 (36223) MWF 1100-1150 ED 2-115 Lab E01 – E09 Thursdays (see BearTracks) BUS B24/28
Contact Info Role Office Email Phone
Ray Hagtvedt Course instructor BUS 2-43 [email protected] (780) 248-1262 Mohua Podder Lab instructor BUS 4-21H [email protected] (780) 492-0393
COURSE DESCRIPTION AND OBJECTIVES
This course incorporates the Learning Goals of the BCom Program. It is meant to follow on STAT 161 or similar, but with a focus on business applications, a goal of understanding the strengths and weaknesses of the methods, and a requirement that Excel become a useful tool for analysis.
Although it is not intended to replicate previous work, repetition and layering will help cement understanding and make it easier to recall data analysis tools when these are required in future coursework and employment. Analytics is a rapidly growing field, and understanding what these tools can, and cannot, do in business is becoming a competitive advantage. This course will therefore review statistics through hypothesis testing, expand the toolbox to include multiple populations, more probability distributions, multiple regression, and introduce additional topics in analytics.
From the Academic Calendar:
This course deals with model building, multiple regression analysis, and related methods useful in a business environment. Computer software will be utilized throughout the course, with necessary computing skills being taught as the course proceeds. However, students are expected to already possess some basic familiarity with microcomputer applications. Prerequisite: STAT 151 or SCI 151. Credit will be granted for only one of MGTSC 312 and STAT 252.
High-level Learning Objectives and Goals – at the end of this course, you should be able to 1. Describe how data analysis fits into the Bachelor of Commerce program, business, and
society at large
2. Acquire, sort, clean, and describe a data-set 3. Create & interpret visual displays of data
4. Use basic probability theory, discrete and continuous random variables, probability distributions, and sampling distributions to solve business problems, such as:
o Find the expected number of bankruptcies a given portfolio of stocks will experience o Find the probability of waiting more than 2 hours at an Emergency Department 5. Analyze samples to draw conclusions to populations, using confidence intervals and
hypothesis tests, and explain how reliable the results are
6. Construct, evaluate and apply regression models to predict one variable based on one or
more other variables
7. Use Excel to (help) analyze data
8. Create final exam questions, for instance to evaluate a regression model
9. Explain to someone who has never taken statistics how to approach an unstructured problem, such as how to estimate the value of electrical power outlets for electrical vehicles in downtown Edmonton. This explanation would include data, methods, and potential problems with the approach you recommend.
COURSE MATERIALS
Required Textbook: Statistics for Business and Economics, 14th edition, by Anderson, Sweeney, Williams, Camm & Cochran (commonly referred to as ASW). Previous editions are fine, but problems will be assigned from the newest edition. ISBN- 9780357031391. We will also use WebAssign, the publisher’s bundled homework tool, and you can find the registration instructions here:
https://www.cengage.com/coursepages/UAlberta_F22_MGTSC312 eClass: You will be able to obtain materials via eClass at:
https://eclass.srv.ualberta.ca/
Other than information provided in class, eClass will be where announcements and other resources regarding the course will be made available. Please check this site regularly and/or make sure your settings in eClass will send you emails when there are updates.
COURSE ACTIVITIES AND EVALUATION
Your grade in this course will be based on the deliverables below. The grades will be weighted as follows to determine your percentage mark in the course:
Assessment Weight
Homework* 10%
Labs* 10%
Midterm Exam** 20%
Excel Exam** 20%
Final Exam 40%
Total*** 100%
* Expect four equally weighted Homework and Lab deliverables, with one component from the lecture and one from the labs, over the course of the semester. Note that there will be only four due dates, but that each due date will have one Lab and one Homework set due.
One assignment each from the homework and labs will be excused, with the weight moved to the other three. This is to facilitate medical emergencies, family crises, or anything else that may (and frequently do) happen to disrupt deliverables.
** The midterm and the Excel exam are both scheduled for Saturdays. Please refer to eClass for specific dates.
*** The total does not include extra credit. Some extra credit may be awarded for participation, to encourage active learning.
Letter grades will be assigned to the percentage marks in accordance with University Regulations [Section 23.4(4) of the University Calendar]. Grades in this course will be based on a combination of absolute achievement and relative performance.
These grades represent the only marks available to students. No additional work or extra credit is available. A limited amount of extra credit may be provided for class participation that benefits the class. No extensions will be granted due to the large number of students.
Missing work for an entire category will have its weight added to the final exam. A single portion will not, so missing a lab will not increase the final exam weight, but will reduce the lab grade. Missing all the labs would increase the final exam weight by 10 percentage points. In order to facilitate flexibility, grades may be calculated multiple ways, but only in such a way that weight is always added to the components considered more difficult, and in particular, the final exam.
In-class activities
Classes are expected to be in-class the entire semester. Attendance at lectures and labs are voluntary, but participation is, of course, encouraged. The midterm and Excel exams are in person, on the dates shown in the schedule. The final exam will also be in person, at the time and place chosen by the university. Details will be made available on eClass.
Online activities
You are responsible for delivering homework and lab assignments online. Unless the university reverts to online-only classes again, no other online activities will be graded. Lab deliverables and the Excel exam will be turned in using the University Online Assessment Tool (see eClass).
Conceptual homework will be made available and due via WebAssign:
URL for homework: https://www.webassign.net/
Class Key: UALBERTA89307195
eClass: https://eclass.srv.ualberta.ca/
Online Assessment Tool: https://apps.srv.ualberta.ca/bus/oa/Course/Details/34 Exams
In-class exams are closed book, closed notes, but with certain tools allowed. Scrap paper, pencils, pens, erasers, & rulers are all allowed. In addition, you will be allowed one 8.5x11 sheet of paper upon which you may write anything in your own handwriting. Writing by hand has (statistically) been shown to be an extremely effective tool for learning, so no alternative to your own handwriting will be accepted, unless you have a documented exception from the university. For the midterm and final exams, you will be allowed a standard non-programmable calculator from the list maintained by the Faculty of Engineering:
https://www.ualberta.ca/engineering/student-services/student-policies/calculator-use- specifications.html
The Excel exam will be taken individually on lab computers with Excel access. All calculations will be performed using Excel only (hand-held calculators will not be allowed for this exam).
Dates and Deadlines:
Homework Set I Friday, September 23, at 2359 Homework Set II Friday, October 14, at 2359 Midterm Exam Saturday, October 22, 1000-1200 Homework Set III Friday, November 4, at 2359
Excel Exam Saturday, November 26 (times TBD)
Homework Set IV Friday, December 2, at 2359 Final Exam Friday, December 9, at 0900-1200 Exams Remarking Policy
Solutions to textbook problems will not be provided, except on the whiteboard. Solutions to the homework will be provided from within WebAssign.
Students should review the grades and raise any questions about grades as soon as possible. No regrading requests will be accepted more than one week after the results have been made
available.
All appeals for regrading must be in writing and the original copy (when available) must be
attached. Exams submitted for appeal will be subject to an entire review by a new grader. This may result in a lowered grade.
Final exams will not be returned, nor solutions posted, but the exams will be available for examination for up to one year after the final exam.
For information regarding applying for a reappraisal of your final exam please see Section (2) of the Calendar.
Link to official U of A grading policy documents:
https://policiesonline.ualberta.ca/PoliciesProcedures/Pages/DispPol.aspx?PID=101 Absences from Exams
Occasionally life events occur that require a student to miss term work, term examinations, or final examinations. However, excused absences are not granted automatically and will be considered only for acceptable reasons such as incapacitating illness, severe domestic affliction, or religious convictions.
Unacceptable reasons include, but are not limited to, personal events such as vacations,
weddings, or travel arrangements. When a student is absent without an acceptable excuse, a final grade will be computed using a raw score of zero for the work missed. Any student who applies for or obtains an excused absence by making false statements will be liable under the Code of
Student Behaviour.
If a student is absent from either the midterm or the Excel exam for a legitimate and adequately documented reason, the weight of the missed exam will be reallocated to a comprehensive final exam. There will be no deferred midterms or Excel exams in this course.
If a student is absent from the final exam, he or she must obtain permission from the
Undergraduate Office to write a deferred final exam. The deferred exam will be written at a time determined by the Undergraduate Office in consultation with the instructor.
Section 23.3(2) and 23.5.6 (1) of the Calendar provides the University Regulations regarding procedures in the case of a missed final examination. If a deferred final exam is required for this course, it will tentatively be held on the Friday before Reading Week at 0800.
ETIQUETTE
Showing courtesy and professionalism to the class and the instructor is an important part of every class. It is expected that students observe business etiquette, and in particular:
a. Will arrive in class before it begins and will stay until it is over;
b. Will not engage in sidebar conversations or otherwise disrupt;
c. Will keep devices off, or at least not audible Class Attendance
Attendance is not required. It is your responsibility to attend class and office hours as you deem necessary.
Email is key to efficient communication, both because it is asynchronous and provides a permanent record, but also because it is simple and private. However, with multiple sections of several different courses, and hundreds of students, the potential for inbox paralysis is high. So please include your course and section in the heading, with perhaps one word about the subject in addition. This will make it much easier to respond to specific questions. Please include all pertinent information, particularly screen shots, so that references to anything are avoided. I will strive to respond to emails with a question or request within 24 hours, unless it is something that resolves itself naturally. Please do not ask for a confirmation, unless you have first asked for one in person during a lecture or office hours.
Changes to policy or special cases
It is your responsibility to make sure that any special cases are documented. Although flexibility and freedom are generally desirable, very large classes require special care that every student is treated identically. As such, no deviations from policy will be accepted without prior permission secured, in writing.
ACADEMIC SUPPORT
The Academic Success Centre provides professional academic support to help students maximize their academic success and achieve their academic goals. The Centre offers appointments,
advising, group workshops, online courses, and specialized programming year- round to students in all university programs, and at all levels of achievement and study.
Location: 1-80 Students' Union Building University of Alberta, North Campus Website: https://www.ualberta.ca/current-students/academic-success-centre Phone: 780-492-2682 Email: [email protected]
ACADEMIC INTEGRITY
Absolute and complete academic honesty is expected of you in this course. It is important for you as a student to behave in an ethical manner. The University of Alberta is committed to the highest standards of academic integrity and honesty. Students are expected to be familiar with these standards regarding academic honesty and to uphold the policies of the University in this respect.
Students are particularly urged to familiarize themselves with the provisions of the Code of Student Behaviour (online at http://www.governance.ualberta.ca/StudentAppeals.aspx) and avoid any behaviour that could potentially result in suspicions of cheating, plagiarism, misrepresentation of facts and/or participation in an offence. Academic dishonesty is a serious offence and can result in suspension or expulsion from the University.
Policy about course outlines can be found in Section 23.4(2) of the University Calendar.
TENTATIVE OVERVIEW of the COURSE SCHEDULE
Note that the schedule below will change as more information becomes available.
Date(s) Topics Chapters
(ASW)
Labs Prior to
course
Review introductory statistics (e.g.
STAT161) 1-9
Cycle 0: Excel Basics
Sept 1-16 Introduction & review Cycle 1:
Introduction to Excel Add-ins: Reading and
summarizing data Sept 18-23 Inferential statistics on two
populations
10 Sept 26-29 Inferences on population variances 11
Oct 3-7 Chi-squared methods 12 Cycle 2:
Pivot & contingency tables;
Probability functions; data simulation; inferential statistics Oct 12-14 Experimental Design and Analysis
of Variance 13
Oct 17-22 Consolidated Midterm Exam on Oct 22; No classes Oct 17-21 Oct 24-28 Review of covariance and
correlation and Univariate OLS regression
3.5, 5.4, 14
Cycle 3:
OLS Regression; dummy and interaction variables; Model
selection Oct 31-Nov 4 Multiple regression 15
Nov 7-11 Reading Week – No classes
Nov 14-18 Model building & Logistic regression 16 Cycle 4:
Logistic regression; Excel and Data Analytics
Nov 21-25 Nonparametric methods 18
Nov 26 Consolidated Excel Exam Saturday, Nov 26
Nov 28-Dec 2 Decision Analysis 19
Dec 5 Artificial intelligence, Machine Learning, and Big Data Dec 7 Open review
Dec 9 Final exam Friday, December 9, 0900-1200
Note that there are no classes on dates the university is closed, including Labour Day (Sept 5), Truth and Reconciliation Day (Sept 30), Thanksgiving Day (Oct 10), and Remembrance Day (Nov 11).
