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Course Code: ANLY620 Course ID: 4877 Credit Hours: 3 Level: Graduate
This course gives emphasis to understanding how the predictive analytic approach flows, as well as the process of analysis starting with a problem, and through effective analytics approach that is cohesive and integrating of various statistical analysis tools for predicting behavior of variables in a modeled relationship. (PREREQUISITE: BUSN662)
|Registration Dates||Course Dates||Session||Weeks|
|03/30/20 - 09/04/20||09/07/20 - 11/01/20||Summer 2020 Session D||8 Week session|
|06/29/20 - 12/04/20||12/07/20 - 01/31/21||Fall 2020 Session D||8 Week session|
LESSONS AND READING
Students are required to actively participate reading and studying of the chapter materials so that they can analyze meaningful data and information by using predictive analytics methods and applications.
There are eight Forum Topics, in which are designed to promote interaction amongst fellow participants and to motivate or provoke other thoughts on the matter. This discussion format allows you to post and respond to other students within the convenient time frame of the weekly schedule. The study subject is graded in accordance with the assigned paragraph length requirements and required responses to at least two of your colleagues’ postings. These postings must add value and expand the conversion on the topic. Correspondent must interact with other participants throughout the Forum exercise to receive full participation credit.
1. The Main Response to the Discussion Question(s) must be written in a substantive manner with no less than 250 words that are relevant to the discussion topic(s). You must also include at least one scholarly source in your researched response.
2. Your interactive post should be at least 150-200 words that expand the conversation forward.
3. Please do not attach your responses, but make sure that you write within the body of the forum.
There is one written assignment per week which is due at the end of the week. Your grades are based on the completion of the assigned assignment in accordance with the instructor’s lesson task requirements, and the use of the APA style guidelines. All the assignments must be uploaded into the Assignment Folder with your Turnitin.com submission results for the grading purpose.
Tests/Quizzes – These assessments will challenge the understanding of the class textbook material by the students. There may be questions from Predictive Analytics: Microsoft Excel’s topics. Assessments are configured as Problem Sets that will contain multiple-choice questions; or true and false, and essay or short answer format.
|Discussion Forum & Participations||20.00 %|
|Week 1 Discussion Forum||2.86 %|
|Week 2 Discussion Forum||2.86 %|
|Week 3 Discussion Forum||2.86 %|
|Week 4 Discussion Forum||2.86 %|
|Week 5 Discussion Forum||2.86 %|
|Week 6 Discussion Forum||2.86 %|
|Week 7 Discussion Forum||2.86 %|
|Case Study Analysis||20.00 %|
|Assignment 3 Week 3-Initializing Forecasting||6.67 %|
|Assignment 4 Week 4 - Predictive Regression and Classification Attributes||6.67 %|
|Assignment 7 Week 7- In-Database Analytics||6.67 %|
|Week 8 Final Assignment||20.00 %|
|Problem Sets||7.50 %|
|Problem Set 1||1.88 %|
|Problem Set 2||1.88 %|
|Problem Set 5||1.88 %|
|Problem Set 6||1.88 %|
|Week 1 Quiz 1||1.88 %|
|Week 2 Quiz 2||1.88 %|
|Week 5 Quiz 5||1.88 %|
|Week 6 Quiz 6||1.88 %|
|Final Exam||25.00 %|
|Final Exam||25.00 %|
Required resources for your course are provided in a course eReserve. Please click here (https://apus.libguides.com/er.php?b=c), enter your course number in the ‘Search for course eReserves’ box, click Go, and then select the course when it appears below the search box. Information included in LibAnswers (https://apus.libanswers.com/) provides download and print options for offline reading of Library ebooks.
|Book Title:||Various resources from the APUS Library & the Open Web are used. Please visit http://apus.libguides.com/er.php to locate the course eReserve.*|
|Book Title:||Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data (Ebook available through the APUS Online Library)|
|Author:||EMC Education Services|
Not current for future courses.