Syllabus

MGMT 462 Managerial Analytics

Zoom and/or Crown 320

 

Fall 2021 August 30,2021 - December 11, 2021

Instructor:      James Miller

E-mail:             jmiller@dom.edu

Cell phone :    847-530-0550

 

Class Location : Crown 320 (Tuesdays and Thursdays 1:00 - 2:15 pm)

Students have the option to attend by Zoom instead of in person.

 

Texts (required):  

 

1. Business Analytics 3rd Edition by James R. Evans and Publisher Pearson. Save up to 80% by choosing the eTextbook option for ISBN: 9780135231715, 013523171X. The print version of this textbook is ISBN: 9780135231678, 0135231671.

2. Computational and Inferential Thinking (no charge)

The Foundations of Data Science

By Ani Adhikari and John DeNero

The contents of this book are licensed for free consumption under the following license:
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).

The book is available at https://www.inferentialthinking.com/chapters/intro.html

The book is also available in PDF form in Canvas

 

 

 

We will use Microsoft Office software, especially Excel, and Access and the Anaconda distribution of Python.  We will also use Microsoft SQL Server which you should not attempt to install on your own machine. All software is available in the Dominican Tech Center. The easiest way to use all the software needed in this course is to connect to the Dominican Server acats2k12.dom.edu. Instructions to do this will be given in the course. You can connect from home or from Dominican.

 

Note: Chromebook computers will not work for many assignments in this course. See this document for a list of assignments that will or may not work with Chromebooks.

 

Course Description: 

Firms can gain a competitive advantage by using data to make better decisions. Many different organizations, including businesses, governments, and non-profits, are now making significant investments in analytics. The objective of this course is to help you understand the field of analytics and be able to put analytics into a business / managerial environment. A secondary objective is to expose the student to basic concepts in Management Information Systems such as Database Management, Cloud Computing, and Big Data. The course will explore

        1. How managers use analytics to formulate and solve business problems and to support managerial decision making.

        2. The Role of Data to help you understand the basis of all analytics

        3. Descriptive Analytics to help you understand what has happened

        4. Predictive Analytics to help you understand trends and predict outcomes

        5. Prescriptive Analytics to help you decide what action you should take

Cases and hands on exercises will be used.  Students will apply tools such as Microsoft Excel, Microsoft Access and SQL, and Python.  

 

 

 

Prerequisites:  (QUAN201 and MGMT301), and (CIS120 or exemption from CIS120)

 

Grading: (Percentages will be updated as soon as all assignments have been entered into Canvas)

Introductory Discussion 1.5%
Texbook Quizzes 20.5%
Homework 70.0%
Exam in Week 11 8.0%
Total of 337 points 100%
Possible 20 bonus points 5.9%

 

 

 

At the end of the course the final  letter grade will be computed as follows:

 

Letter Grade
 
Corresponding Percentage

A:

 

93-100%

A-:

 

90-92.9%

B+:

 

88-89.9%

B:

 

80-87.9%

C+:

 

78-79.9%

C:

 

70-77.9%

C-:

 

68-69.9%

F:

 

0-67.9%

 

 

 

Logistics:

You will need to use your Dominican e-mail address in this class. Please see the Computer Lab aides if you do not already have the required accounts. Use of Canvas is required.

 

All assignments are due at midnight Sunday night. If you have been "stuck" on an issue for more than 15 minutes, seek help. You are welcome to seek help form me.

 

If you have a reason why your assignment will be late, contact me before the due date. This is easy to do and it could save you the minimal late penalty. The late penalty is 1% per day if you don't ask for an extension ahead of time. So, for example, if your assignment is eight days late it will be mathematically impossible to get an "A" on that assignment.

 

Exam in Week 11:  The exam will cover all materials presented in class up to the exam date.  An emphasis will be placed on the class lectures, notes, handouts and the required reading.  If you must miss the exam, you must obtain approval before the exam date. The exam may be made up on a mutually agreeable schedule but make up dates generally are before the scheduled exam date.

 

Online work (Canvas): All work in this course will be submitted in Canvas (No paper!).

 

Schedule details: The schedule is subject to change. A detailed schedule by class week can be found in Canvas. A summary schedule appears later in this document.

 

 

Objectives: 

Week-by-Week Class Schedule

Week Unit/Chapter Comments Start End
1 U1, Appendix A1 Introduce yourself, connect to remoteapp, Excel Basica 30-Aug 5-Sep
2 U1, Chapt 1 pivot tables 6-Sep 12-Sep
3 Unit 2  Bumping Passengers, Relational Databases 13-Sep 19-Sep
4 U2, Chapt 2 Microsoft Access Database Queries 20-Sep 26-Sep
5 Unit 3 What is Python, SQL Reading tables 27-Sep 3-Oct
6 U3, Chapt 3 SQL Group By, Pivot Tables, SQL Updating tables 4-Oct 10-Oct
7 U4, Chapt 4 Python Quiz 1, Excel descriptive statistics 11-Oct 17-Oct
8 Unit 4 Python USDA Assignment 18-Oct 24-Oct
    Mid Semester Break 25-Oct 31-Octr
9 Uint 5 Excel Regression, Cenus quiz, Easy midterm quiz 1-Nov 7-Nov
10 Unit 5 Why Python and Python Hyundai(Elantra)Sales 8-Nov 14-Nov
11 Unit 6  Two part Exam 15-Nov 21-Nov
12 U6, Chapt 8 P values, Excel Trendline, Jury Pool Selection 22-Nov 5-Dec
13 U7,Chapt 13 TED talk on use of data 29-Nov 5-Dec
14 Unit 7 Linear programmng, optional machine earning 6-Dec 11-Dec
14 Unit 7b Optional machine learning (k-means, k-nearest)   11-Dec
15 Unit 8 Optional Tableau, Optional Crime data   11-Dec
    ALL WORK DUE.   11-Dec

 

 

 

 

Fall Semester 2021

August 30

First Day of Classes for Fall (15 weeks) & Fall I (8 weeks)

September 3

Last day to apply to graduate in Fall 2021

September 6

Labor Day - No Classes

September 7

Add/Drop deadline: Fall undergraduate courses & all Fall I courses

September 14

Add/Drop deadline: Fall graduate courses

September 14

Last day to declare satisfactory/fail grade option for undergraduate courses

September 21

Caritas and Veritas Day (class schedule suspended)

September 24

Last day to declare course intensification option for undergraduate courses

October 21

Last day of Fall I courses (8 weeks)

October 22-24

Long Weekend (no undergraduate classes)

October 25

First Day of Classes for Fall II (8 weeks)

November 1

Add/Drop deadline: all Fall II courses

November 5

Last day to withdraw from Fall courses (15 weeks)

November 24-28

Thanksgiving Vacation

December 11

Last day of Fall and Fall II undergraduate courses

December 13-18

Undergraduate Final Examinations

December 18

Last day of Fall and Fall II graduate courses

December 21

Final Grades due at noon for all courses

January 8

Fall Degree Conferral