MGTSC 312 Course Outline Winter Term 2014 Alberta School of Business
Department of Finance and Statistical Analysis Lecture Section B1: Tuesdays and Thursdays, 2:00-3:20 PM, Bus 3-6 Lab Section H1: Thursdays, 12:30-1:20 PM, Bus B-28
Instructor: Phil Davidson Email: [email protected]
Office: BUS 1-23B Phone: 780-492-7818
Office hours: MWF 10 – 11, TR 3:30 – 5, e-mail for appointment, or try your luck
The various topics in this course build on previous topics, so don’t get behind. If you are having difficulty please discuss with your instructor immediately.
Introduction: This course will help you learn how to access the wealth of data available online, how to analyse that data using Microsoft Excel, and how to interpret the results. We will look first at descriptive statistics, then at one-sample inference for the population mean and proportion. The bulk of the course will focus on regression. Developing facility in the use of Excel to manipulate and analyze data will prove to be a very useful skill in later courses and in your working life. The ability to interpret results and explain them to others is a valuable business skill.
Software: We will use Office 2010 for Windows in classrooms and labs. Office 2007 or 2013 should also work without significant problems. If you use a Mac and have problems, we are not in a position to help with those and do not have Mac versions of the course materials that are in electronic form. We also recommend that you use a Windows machine for practice materials since that is what you will use in the labs and for exams.
Course pack: There is a required course pack, customized to the needs of our program and that is far less costly than the commercial textbooks for this sort of course. It is sold by the OM Club for $30 on a no- refund basis in the first week of the term.
Notes and Schedule: I will post slides, data sets, and other materials for lectures under Lectures on uLearn. It is helpful to review the notes before class. The Syllabus and Schedule page on uLearn includes dates and topics for lectures, labs, exams, and assignments. Dates for exams will not change, but dates for assignments are tentative until an assignment is made available to work on.
Tutorial: An online self-paced tutorial covering the earlier material of the course is available at http://apps.business.ualberta.ca/mgtsc312. It is new and still incomplete, but has quite a bit of material.
Practice Problems: I will post practice materials and solutions on uLearn.
What you should be able to do at the end of the course:
• Understand applied articles, reports, textbook materials, and lectures in other courses that make use of descriptive statistics, correlation and regression analysis, and statistical inference for the mean, correlations and standard regression parameters.
• Locate, manipulate and analyse real data from existing online sources using Microsoft Excel.
• Compute descriptive statistics, correlations and regressions; carry out statistical inference for parameters of interest.
• Use Excel formulas, functions, tools and wizards, including pivot table, auto filter, the data analysis toolbox, etc.
• Create effective graphs.
• Find and interpret values in computer output: Values of test statistics, p-values, parameter estimates, confidence intervals, etc.
• Write up the results of statistical analyses of data.
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MGTSC 312 Course Outline Winter Term 2014 Class participation: Participation in the lectures, including class discussions, and labs is essential.
Students who often come late or leave early, or who miss many lectures or labs are not able to participate fully when they do attend. In most class periods when there is no scheduled graded quiz, there will be an ungraded quiz. The papers will be collected and attendance for the class period will be based on the papers collected. Via this classroom participation, you can earn up to 1/2% per week (up to 6% in total) toward your final mark by completing all these quizzes. Looking at these ungraded quizzes helps me know if there are points that quite a few students have not understood properly.
Evaluation:
• Four exams: each worth 17% (68%), all in the lab
• Two assignments: assignment 1 worth 10%, assignment 2 worth 16% (26%)
• Ungraded quizlets in most lectures, full mark for submitting, regardless of the answers, 1/2% per week (6%)
• If you miss an exam with a valid excuse then its weight will be transferred to other similar evaluations
• Your letter grade will be determined primarily by your relative standing in the course. The grade distribution will be similar to other 2nd year courses at the University of Alberta, with an average of approximately B
Students who require accommodations in this course due to a disability affecting mobility, vision,
hearing, learning, or mental or physical health are advised to discuss their needs with Specialized Support and Disability Services, 2-800 Students' Union Building, [email protected], 492-3381 (phone) or 492-7269 (TTY).
Policy about course outlines can be found in §23.4(2) of the University Calendar.
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/CodesofConductandResidenceCommunityStandards/CodeofStudentB ehaviour.aspx) and avoid any behaviour which 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.
The assignments are individual assignments. Each student is expected to do their own computing and write their own report. Evidence of cooperation will result in a score of zero for the assignment to the cooperating students. Both the giver and receiver will be assigned the score of zero. Additional sanctions are possible.
Learning Resources: We want to provide you with as many resources as possible to help you succeed in this course. We have lectures and normally post the lecture slides before we begin each topic in class. We have labs and normally post both lab slides and solution Excel files. We have a custom course pack. We have an online, self-paced tutorial which covers much of the basic material you need to know (new this year but somewhat incomplete). We post additional practice materials on uLearn. We have committed course resources to subsidize tutors and study-buddies, in conjunction with the OM club.
Classroom and Lab Etiquette
Attendance: It is your responsibility to attend lectures and labs. If you miss class for any reason, you are still responsible for all materials covered and announcements made.
Be on time for lectures and labs and remain for the entire period. Arriving late or leaving early is
inconsiderate of other students. If you have a valid reason for coming late or leaving early, please discuss that with your instructor.
Conversations: Do participate in class discussions and active learning exercises, as prompted by your instructor. Do not engage in sidebar conversations at other times, to avoid distracting other students or the instructor.
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MGTSC 312 Course Outline Winter Term 2014 Breaks: You should not normally leave or re-enter the classroom or lab during the class period. Doing this is disruptive to fellow students and to the instructor. If you are affected by illness or medication such that you realize it may be necessary for you to leave during the class period, then please arrive early enough to sit close to the door so that you can leave and return with a minimum of disturbance.
Cell Phones: All cell phones, pagers, Blackberries, iPods, and similar communication devices must be turned off for the duration of the class. Text messaging or emailing, after the start of class, is not permitted.
Laptops: Some students find it useful to use a laptop during lectures to take notes or perform analysis that the instructor is demonstrating. Laptop usage during class for this purpose, and for viewing PowerPoint slides, is permitted, but with the following caveats:
• Laptops are not permitted during exams
• If you use a laptop, then be considerate of students around you and behind you
• Using a laptop for email or other non-class purposes during lectures or labs is not permitted Recording of Lectures or Labs: Recording is permitted only with the prior written consent of the professor or if recording is part of an approved accommodation plan.
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MGTSC 312 Course Outline Winter Term 2014 Approximate Schedule
Week Lecture Topics Reading Lab Evaluation
1
Jan. 6 - 10
Datasets
Descriptive Statistics Topic 1 slides Excel basics Course Pack sales 2
Jan. 13 - 17
Descriptive Statistics Probability and Sampling
Crs Pk Ch 1, 2, 3, 4
Accessing online data Course Pack sales 3
Jan. 20 - 24
Confidence intervals for one mean or proportion
Ch 5
Topic 2 slides
Manipulating data Descriptive statistics 4
Jan. 27 - 31
Hypothesis tests for one mean or proportion
Ch 6
Topic 3 slides Exam Exam 1
5
Feb. 3 - 7
Inference for population
variance and standard deviation, Covariance and Correlation
Ch 7, 9 Topics 4 & 5 slides
Graphs
Probability Functions 6
Feb. 10 - 14 Simple Linear Regression Ch 10
Topic 6 slides
One-sample Inference Covariance &
Correlation
Feb. 17 - 21 Reading Week No Classes
7
Feb. 24 - 28 Simple Linear Regression cont. Exam Exam 2
8
Mar. 3 - 7 Multiple Regression Ch 11
Topic 7 slides
Manipulating data Regression tool
Assignment 1 due 9
Mar. 10 - 14
Multiple Regression,
Multicollinearity, violations of assumptions
Multiple Regression, Multicollinearity, Residual Plots 10
Mar. 17 - 21
Categorical variables in regression
Ch 12, 13 Topics 8, 9 &
10 slides
Exam Exam 3
11
Mar. 24 - 28
Categorical variables cont.
Time Series Analysis
Ch 14
Topic 11 slides
Partial F, Categorical variables
12
Mr 31 – Ap 4
Time Series Analysis cont.,
Term Paper questions Exam Exam 4
13
Apr. 7 - 9 Term Paper questions
Apr. 11 Term paper
4