This course will introduce students to key analytic methods dealing with statistics, probability, and forecasting. By the end of the course, students will be able to understand and employ common analytical methods themselves as well as being well-informed customers of more advanced analytics teams in their organizations. Methods will be explored each week through readings and videos, with assigned problems, online discussions, a midterm exam, and the option to finish the course with a mini-project or a final exam. The programming language, R, will be the tool of choice for this course though some work can be completed in Microsoft Excel, and Python will also be supported.
The latest DRAFT of the syllabus is available here: GSCM571_DRAFT_Syllabus.pdf
Course is delivered via D2L. Lectures will be delivered asynchronously, and quizzes, discussions, and lab exercises will have published due dates.
A synchronous optional office hour is arranged with students that can be attended in-person (if local) or remotely, and is recorded for later listening/viewing as needed. Additional office hours will be primarily by-arrangement.
The texts for this course are available in physical hard-copy as well as freely available online PDFs or web-pages. The following texts are required in the sense that we’ll have assigned readings and problems from them. Students are not required to use the hard-copy versions.
The tables below show the main grading items and their percentage of the total grade.
| Required.Grade.Item | Grade.Percent |
|---|---|
| Introduction Discussion | 5 |
| Midterm Exam | 15 |
| Group Session #3 | 5 |
| Mini-Project OR Final Exam | 25 |
| TOTAL | 50 |
The grade-book is structured so that a number of the Weekly Assignments, Online Discussions, and Group Sessions can be dropped and full-points will still be availability (“life happens!”)
| Flexible.Grade.Item | Number.Avail | Suggested | Points.Each | Points | Max.Points |
|---|---|---|---|---|---|
| Weekly Assignments | 7 | 5 | 5 | 25 | 35 |
| Online Discussions | 6 | 4 | 5 | 20 | 30 |
| Group Sessions (1-2) | 2 | 1 | 5 | 5 | 10 |
| TOTAL | 50 | 50 (of 75) |
Standard grading scales used in the SBA are used in this course.
| Letter.Grade | Points |
|---|---|
| A | 94-100 |
| A- | 90-93.99 |
| B+ | 87-89.99 |
| B | 84-86.99 |
| B- | 80-83.99 |
| C | Below 80 |
For the most part, Weekly Assignments will be a set of problems to be solved and submitted as a Quiz on D2L. You’ll be able to re-submit as many times you like until the due date. A few assignemnts may be some product that needs to be turned in via Assignments on D2L.
The grade-book is set up so that you skip 2 Weekly Assignments and still acheive full marks for the course. You may also opt to complete all of the Weekly Assignments and then you’ll be able to complete fewer Weekly Discussions.
The problems assigned in the Weekly Assignments are nearly identical to the questions that will appear in the Midterm and Final Exams.
Weekly Discussions will be drawn mostly from the assigned readings from “Statistics Done Wrong” text.
The grade-book is set up so that you skip 2 Weekly Discussions and still acheive full marks for the course. You may also opt to complete all of the Weekly Discussions and then you’ll be able to complete fewer Weekly Assignments.
There is a Midterm (Week 6) for the course that will be delived on D2L (as a quiz). The questions on the Midterm will be very similar to the questions assigned in the Weekly Assignments. If you do well on the Weekly Assignments, you should do well on the Midterm.
After the Midterm, students may then choose to either take a Final Exam or work on a Mini-Project.
The final will be cumulative and will work just like the Midterm; a Quiz item delivered on D2L.
If you are interested in exploring a particular problem (or NOT interested in taking the Final), students can opt to complete Mini-Project. A proposal is due the week after the Midterm, with deliverables (inlcuding a small presentation) due during Finals week.
Students who originally decide to do a Mini-Project may decide to switch back to taking the Final Exam at any point in the remainder of the term.
The table below shows the general plan and schedule for the course.
| Week | Topic | Activity | Due |
|---|---|---|---|
| 1 | Introduction: Analytics as a process and product, R & RStudio. Overview of data and methods. | Discussion 1 | Install R/RStudio, post “hello world” |
| 2 | Exploring Data: Distributions of Single Variables, Relationships among variables | Discussion 2 | Assignment 1 |
| 3 | Probability & Distributions; Normal, Binomial, Poisson, Exponential | Discussion 3 | Assignment 2 |
| 4 | Sampling, Sampling Distributions, Confidence Intervals | Group Session #1 | Assignment 3 |
| 5 | Hypothesis Testing | Discussion 4 | Assignment 4 |
| 6 | Midterm Prep | Midterm Exam / Mini-Project Proposal | |
| 7 | Regression Analysis: Estimating Relationships and Statistical Inference | Group Session #2 / Discussion 5 | Assignment 5 |
| 8 | Forecasting & Time Series Analysis | Discussion 6 | Assignment 6 |
| 9 | Logistic Regression (binary and categorical variables) | Discussion 7 | Assignment 7 |
| 10 | Machine Learning & AI | Group Session #3 | Mini-Project Presentation |
| 11/Finals | Final Exam or Project Write-up | Final Exam, Mini-Project Writeup |
No, but it can be moderately helpful.
In many cases the problems in this course can be worked using merely Excel. However one goal of this course is to develop competency at using R to do basic statistical work. However this will not require extensive programming - most problems will be handled with a couple lines of code. Many examples of doing these kinds of analysis will be made available throughout the class.
We’ll also support using Python for the statistical work for those who have that preference.
No. All the books assigned in this course are freely (and legally) available online as either web-pages or PDFs.
You may choose to buy the hard-copy versions but this is not required. They are also available online but may also be available through the PSU Bookstore.