Please note that this is a tentative schedule. Some of the topics, assignments and exercises are likely to be changed due to the pace of discussion of the scheduled topics in each class/lab. Also, there may be some cases (mini and large) assigned for some of the weeks that are not shown in the schedule and will be announced via D2L or in-class. For each topic, I have also identified some of the readings that correspond to my video lectures. But, you can find pretty much all of the definitions of terms, explanations of most the statistical stuff that I discuss in the lecture on the Internet (Wikipedia and other credible sources). So, be proactive and go learn on your own if you are unclear about any topic covered in the video lecture. I expect you to be prepared for each session and be able to discuss and participate in the lab sessions (non-DL students). The cases/assignments/exercises/projects will be announced in labs and/or via D2L class site. All changes in the schedule will be communicated to you in class and/or via D2L class site. Readings, exercises, assignments, projects, etc. will be assigned and posted on the D2L class site and/or announced in the labs. It is your responsibility to check D2L site every week for changes or announcements with respect to schedule, exercises, assignments, project, readings etc. Note about Exercise and Labs: Expect something to do (exercise, assignments, case, etc.) in each lab session. Any item due in week ‘t’ assumes that you must have reviewed lecture videos up to week ‘t1’ and lab videos up to week ‘t-1’. So, for example, Exercise 1 is due in Week 3. Therefore, I will assume that before doing Exercise 1, you must have reviewed lectures up to week 2 and also reviewed lab videos up to week 2. For DL students, exercise/assignment of any week is due on Monday of that week by 2:30 PM US CST via appropriate drop box. For non-DL students, generally exercises will have to be done during the lab session (Monday) for that week unless mentioned otherwise in the schedule or announced on D2L.
Week# 1 (Week begins on Aug. 19)
Video Lecture Topics and Associated Readings: • Part 1: Course introduction, course expectations and course requirements. • Part 2: An overview of analytics and data mining certificate program options at OSU, recommended courses and recommended certifications (http://analytics.okstate.edu/ ) • Part 3: An overview of state of analytics (http://www.sas.com/businessanalytics/, http://www.accenture.com/us-en/consulting/analytics/Pages/index.aspx,) • Part 4: A quick look at using SAS (http://support.sas.com/ ) Lab and Exercises: • No designated lab or exercise this week. Nothing to turn-in (yippee!.) but practice using SAS based on what I showed in the lecture videos
Week# 2 (Week begins on Aug. 26)
Video Lecture Topics and Associated Readings: • Part 1: Basics of Marketing, B2B versus B2C marketing, Direct versus Indirect marketing, (http://www.marketingpower.com/aboutama/pages/definitionofmarketing.aspx , http://www.marketingedge.org/ ), An overview of STP (segmentation, targeting and
positioning) strategies in marketing, 4P’s of Marketing Mix, Different Types of Segmentation (http://en.wikipedia.org/wiki/Segmenting_and_positioning, http://www.census.gov/ , http://www.claritas.com/MyBestSegments/Default.jsp) • Part 2: Modern versus traditional view of statistics (http://www.statisticsviews.com/details/feature/4892951/Statisticians-are-the-modernexplorers_-An-interview-with-Professor-David-J_-Han.html) , • Part 3: Important concepts in statistics such as population and sample, parameters and statistics (http://www.stats.gla.ac.uk/steps/glossary/basic_definitions.html#popn ) , sampling and non-sampling error, etc., (http://en.wikipedia.org/wiki/Sampling_error), Collecting data (primary versus secondary, experiments versus post-hoc), types of data (quantitative versus qualitative) and scales of measurement such as