1
WILMINGTON UNIVERSITY
COLLEGE OF BUSINESS
COURSE SYLLABUS
(Version 8/23/2020)
Course Title: Survey of Data Analytics
Course Number: MBA 6350 (DISTANCE)
Pre-Requisites: 3 cr. undergraduate algebra, calculus, or statistics (MAT 110 or higher)
Term: Fall 1 – 2020
Faculty Member: Dr. Michael Einstein
Faculty Contact Information: Email: Michael.M.Einstein@wilmu.edu
Method of Contact: As Requested; via Email, telephone, or WEBEX/Collaborate
Textbook: Business Statistics: Communicating with Numbers, Jaggia & Kelly, 3rd
Ed., with McGraw-Hill Connect.
Textbooks can be purchased at the Wilmington University Campus
Bookstore
McGraw-Hill Connect: Purchase of a McGraw-Hill Connect access code is a required aspect of
this course (included with “new” textbooks or purchased separately
from McGraw-Hill publishing).
Check Canvas for the Connect registration link for your course section.
Chapter homework and quizzes, are completed weekly using McGraw–
Hill Connect online system.
Canvas: Canvas will be used for all class communications, exams, and final
grades. Please check it often!
Course Technical Requirements:
● A headset or microphone.
● A webcam.
● Access to Microsoft Excel with full functionality.
Supplemental Resources/Links:
● Stat Trek – Teach yourself Statistics
● Dr. Arsham’s Statistics Site
● Excel Easy
● Using the Analysis ToolPak
● Statistical Tool in Excel
COURSE DESCRIPTION:
This course is an introduction to data analytics, which involves using statistical analysis and
visualization techniques to describe, display, and explore data to develop useful insights and convert
data to actionable information that enables learning and making better decisions. Topics covered
include: data-driven decision-making, Microsoft Excel basics, data visualization (graphical and
tabular), descriptive statistics, pivot tables and charts, correlation analysis, and linear regression
(simple, multiple, and hierarchical). This course emphasizes using the advanced analytic capabilities
of Microsoft Excel.
MAJOR INSTRUCTIONAL GOALS and LEARNING OBJECTIVES:
GOAL A:
Students will master the use of commonly used data analytics and visualization techniques to
describe the relationships between variables in complex data.
Learning Objectives: The student will
A-1 Identify appropriate data analytics and visualization techniques for a given business
decision-making scenario, including data visualization (graphical and tabular),
descriptive statistics, pivot tables and charts, correlation analysis, analyzing
differences between groups, and linear regression (simple, multiple, and
