OSM 202 Intro to Business Analytics

OSM 202 Intro to Business Analytics

Section 50

Cleveland State University

Monte Ahuja College of Business

Instructor Dr. Avinash Geda Phone 352-281-9122
Office BU 546 E-mail a.geda@csuohio.edu
Office Hours Tuesdays and Thursdays: 4:30pm-5: 30 pm Or By Appointment Course Prerequisite Classroom BUS/OSM 201 (or equivalent) with a passing  grade of C or better BU 17A

Textbook:

Bowerman, Bruce L., O’Connell, Richard T., Murphree, Emily S. (2016). Business Statistics in Practice 8e. Includes MegaStat and Connect access (Select material from Business Statistics in Practice 8e). ISBN:978-1-259-54946-5.

Megastat and Connect are both required for this course.

NOTE: You must have a licensed copy of Excel installed on your computer in order for the MegaStat add-in to work. MegaStat works with all recent Windows®-based versions of Excel including Excel 2016. If you have a Macintosh® computer system MegaStat will function with Excel Mac: 2016, 2011 and Mac OS X.

Course Catalog Description:

Application of statistical methods to business problems; topics include chi-square analysis, the F distribution, one-way and two-way analysis of variance, correlation analysis, simple and multiple regression analysis, and introduction to forecasting with regression models; use of computer programs in solving statistical problems.

Connect Course Registration:

 Directions will be provided in class on how to connect to Connect using Blackboard.

Goals:

The students will learn:

  • To identify the necessary and correct statistical tests to help in decision making in personal life or in the business world,
  • The theory behind certain statistical tests to be able to use them efficiently and correctly,
  • To perform these statistical tests using Excel and Megastat and interpret the results to reach conclusions.

Resources:

All PowerPoint presentations and Excel files will be uploaded on the Blackboard site.

Evaluation:

Exam 1                           25%

Exam 2                           20%

Final Exam                     30%

Homeworks                   25%

Grading Scheme:

A=100% – 94%

A-=93.99%-90%

B+=89.99%-87%

B=86.99%-83%

B-=82.99%-80%

C+=79.99%-77%

C=76.99%-70%

D=69.99%-60%

F < 60%

Instructor reserves the right to curve the grades.

Course Schedule:

Date Topics Covered Chapter Reading
27-Aug-19 Introduction – Review
29-Aug-19 Confidence Intervals – Review Chapter 8
3-Sep-19 Hypothesis Testing – Review Chapter 9
5-Sep-19 Statistical Inferences Based on Two Samples Chapter 10
10-Sep-19 Statistical Inferences Based on Two Samples Chapter 10
12-Sep-19 Statistical Inferences Based on Two Samples Chapter 10
17-Sep-19 Statistical Inferences for Population Variances Chapter 9 (p. 418)
19-Sep-19 Statistical Inferences for Population Variances Chapter 9 (p. 418)
24-Sep-19 Statistical Inferences for Population Variances Chapter 9 (p. 418)
26-Sep-19 Review for Exam 1
1-Oct-19 Exam 1 Chapters 9, 10
3-Oct-19 Experimental Design and Analysis of Variance Chapter 11
8-Oct-19 Experimental Design and Analysis of Variance Chapter 11
10-Oct-19 Experimental Design and Analysis of Variance Chapter 11
15-Oct-19 NO CLASS – Columbus Day
17-Oct-19 Review for Exam 2 Chapter 11
22-Oct-19 Study for Exam on your own (Help from Tutor) Chapter 11
24-Oct-19 Exam 2 Chapter 11
29-Oct-19 Chi-Square Tests Chapter 12
31-Oct-19 Chi-Square Tests Chapter 12
5-Nov-19 Chi-Square Tests Chapters 12
7-Nov-19 Chi-Square Tests Chapters 12
12-Nov-19 Simple Linear Regression Analysis Chapter 13
14-Nov-19 Simple Linear Regression Analysis Chapter 13
19-Nov-19 Simple Linear Regression Analysis Chapter 13
21-Nov-19 Multiple Regression and Model Building Chapter 14
26-Nov-19 Multiple Regression and Model Building Chapter 14
28-Nov-19 NO CLASS – Thanksgiving Recess Chapter 14
3-Dec-19 Multiple Regression and Model Building Chapter 14
5-Dec-19 Review for Final Exam Chapters 12,13,14

*The schedule is tentative, the instructor reserves the right to make changes as the class progresses.

Examinations:

There will be 3 exams. Exam 1 will cover the material from Chapters 9-10, Exam 2 will cover Chapter 11, and the final exam will cover Chapter 12-14. Exams will be in class and closed notes, closed books. Students are allowed 2 cheat sheets (A4, front and back). No cell phones or talking allowed.

Makeup exams will be provided only in the case of DOCUMENTED emergencies.

Homeworks:

The exact due dates and times for homework will be available through connect.

All homework will be through Connect. It is the students’ responsibility to check the Blackboard website for homework due dates! Homework makes up 25% of your grade!!!!

Instructor:

Avinash Geda is a Visiting Assistant Professor in the College of Business in Operations and Supply Chain Management Department. He received his Ph.D. in Operations Management from the University of Florida, MS in Civil Engineering with a focus on Transportation Engineering from the University of Florida, and his Bachelor’s degree in Civil Engineering from The National Institute of Technology. He has taught classes covering the subjects: Demand Forecasting, Newsvendor Analysis, Queueing Theory, Supply Chain Coordination, Decision Analysis, Revenue Management and Project Management. His current research interests include socially responsible operations and e-commerce operations. His research employs optimization, game theory and other economic models.

Retention of Student Work:

The professor reserves the right to retain for pedagogical reasons the original, or a copy, of a student’s test, written assignment, paper, video, or similar work (including individual and group projects) submitted by the student for this class.

Student Conduct

Students are expected to do their own work. Academic misconduct, student misconduct, cheating, and plagiarism will not be tolerated. Violations will be subject to disciplinary action as specified in the CSU Student Conduct Code. A copy can be obtained on the web page at http://www.csuohio.edu/studentlife/StudentCodeOfConduct.pdf, or by contacting Valerie Hinton Hannah, Judicial Affairs Officer in the Department of Student Life.

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