Business Analytics at LSSU C. Christopher Lee Associate Professor of Management Business Analytics at LSSU Presented by C. Christopher Lee Associate Professor.

Slides:



Advertisements
Similar presentations
Overview of Quantitative Finance and Risk Management Research By Dr. Cheng-Few Lee Distinguished Professor, Rutgers University, USA Distinguished Professor,
Advertisements

Islamic University in Gaza Faculty of commerce Business Administration Department (BUSE 4302) Operations Research Instructor: Hani Abuamer Office Hours:
STATISTICS TUTORIAL Applied Research In Organizational Behavior By: Dr. Goli Sadri.
Integrating Japanese History Into An Operations Management Course Japan Studies Institute San Diego State University San Diego, California June 2-20, 2008.
Review of the fundamental concepts of probability Exploratory data analysis: quantitative and graphical data description Estimation techniques, hypothesis.
MGMT 302 ONLINE Course Introduction. Textbooks William J. Stevenson, 8 th edition Richard D. Irwin, 2004.
Statistics for the Social Sciences Psychology 340 Spring 2005 Course Review.
The Practice of Social Research
Adapting to Different Audiences Chris Lowery and Bill Miller Georgia College & State University.
Career in Management & Management Major at LSSU Dr. C. Christopher Lee Dr. Madan Saluja Dr. Linda Schmitigal-Snyder Career in Management & Management.
Research Terminology for The Social Sciences.  Data is a collection of observations  Observations have associated attributes  These attributes are.
Quantitative Methods of Management
Department of Business Information & Analytics MSMESB: Experience with Adding Analytics to the Academic Program Kellie Keeling University of Denver.
Satish Nargundkar Georgia State University Presented at the Decision Sciences Institute Annual Meeting, Baltimore, Nov , Business Analytics.
Title Author Names Author Pictures Faculty Advisor: C. Christopher Lee, PhD Lake Superior State University Spring 2014.
Associate Professor Arthur Dryver, PhD School of Business Administration, NIDA url:
A Flight Plan for Studying Statistics. The Scientific Procedure 1) Concepts (empirical and hypothetical) 2)Operational Definitions (measurement and procedure)
Advanced Higher Statistics Data Analysis and Modelling Hypothesis Testing Statistical Inference AH.
Part 0 -- Introduction Statistical Inference and Regression Analysis: Stat-GB , C Professor William Greene Stern School of Business IOMS.
WHAT TO DO WITH A MAJOR IN… OPERATIONS MANAGEMENT Presented by: Kellie Klinck, M.A., L.L.P.C., N.C.C. Academic Adviser, School of Business Administration.
Managerial Decision Analysis  Survey results  Course curriculum development.
MBAA 607- Operations Analysis & Decision Support Systems Spring 2008 Tuesday 4:25-7:05 Dr. Linda Leon.
MBAA 607- Operations Analysis & Decision Support Systems Spring 2011 Monday 4:25-7:05 Dr. Linda Leon
Supply Chain Management
A.Quantitative Modelling & Simulation: Objectives: To: - Create awareness on modelling techniques; it’s benefits and the way to use them - Provide training.
1 1 Slide © 2005 Thomson/South-Western MANAGMENT SCIENCE n Chapter 1: Introduction Problem solving and decision making; quantitative analysis and decision.
Agenda of Week I. Introduction Modules  Office and contact point  Education  Research interest Lecture Issues Professor Introduction 123  Lecture site.
The Purpose of Statistics (Data Analysis)
Management Science Helps analyze and solve organizational problems. It uses scientific and quantitative methods to set up models that are based on controllable.
Psychology 202a Advanced Psychological Statistics November 12, 2015.
1 Beginning & Intermediate Algebra – Math 103 Math, Statistics & Physics.
Business Analytics Skills
New Information Technologies in Learning Statistics M. Mihova, Ž. Popeska Institute of Informatics Faculty of Natural Sciences and Mathematics, Macedonia.
Beginning Statistics Table of Contents HAWKES LEARNING SYSTEMS math courseware specialists Copyright © 2008 by Hawkes Learning Systems/Quant Systems, Inc.
Stats Term Test 4 Solutions. c) d) An alternative solution is to use the probability mass function and.
Review of BUSA3322 Mary M. Whiteside. Methodologies Two sample tests Analysis of variance Chi square tests Simple regression Multiple regression Time.
Multivariate Analysis
Chapter 2 Six Sigma Installation
William J. Miller Christopher M. Lowery
Teaching Statistics Courses in the Wave of Business Analytics
Part Three. Data Analysis
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Production Management
Business Analytics: Making Your Data Count
The Modeling Process Objective Hierarchies Variables and Attributes
Experiences with Business Analytics Curriculum Implementation
The Business Analytics Program at Old Dominion University
Session 2:50 PM - 4:20 PM; Saturday, Nov 18, 2017
Experiences and Lessons Learned from UNC Wilmington
IME634: Management Decision Analysis
Cases. Simple Regression Linear Multiple Regression.
Islamic University in Gaza Faculty of commerce Business Administration Department (BUSE 4302) Operations Research Instructor: Hani Abuamer Office Hours:
Presentation transcript:

Business Analytics at LSSU C. Christopher Lee Associate Professor of Management Business Analytics at LSSU Presented by C. Christopher Lee Associate Professor of Management

Business Analytics Quantitative Management Quantitative Management Research Methodology Research Methodology Scientific, Objective, Quantitative Analysis Scientific, Objective, Quantitative Analysis 3 Major Areas of Business Analytics: 3 Major Areas of Business Analytics: –Business Statistics –Management Science –Management Information Systems Job Opportunities: Job Opportunities: –800 job openings at Wal-Mart

Biz. Analytics Curriculum at LSSU Biz. Analytics 2 - BUSN 211, Business Statistics Biz. Analytics 3 - MGMT 280, Management Information Systems Biz. Analytics 4 - MGMT 371, Operations & Business Analytics (formerly MGMT 375, Supply Chain Management) Biz. Analytics 5 - MGMT 471, Advanced Business Analytics (formerly MGMT 375, Supply Chain Management) Biz. Analytics 1 - BUSN 122, Biz. Applications with Contemporary Technologies Prerequisites - College Algebra

Business Analytics 2 - BUSN 211, Business Statistics Descriptive Statistics Descriptive Statistics Data Mining Data Mining Sampling Theory Sampling Theory Statistical Inference Statistical Inference Central Limit Theorem Central Limit Theorem Hypothesis Testing Hypothesis Testing T-Test Model T-Test Model ANOVA Model – One Way ANOVA ANOVA Model – One Way ANOVA Regression Model - Simple Regression Regression Model - Simple Regression 4

Business Analytics 3: MGMT 280, Management Information Systems Systems Theories Systems Theories Database Design, Administration Database Design, Administration Decision Support Systems Decision Support Systems Data Warehousing Data Warehousing Data Mining Data Mining Systems Development Life Cycles (SDLC) Systems Development Life Cycles (SDLC) System Implementation – Project Management of Information Systems Development System Implementation – Project Management of Information Systems Development Big Data – Concept, Analysis, Models Big Data – Concept, Analysis, Models 5

Business Analytics 4: MGMT 371, Operations & Biz. Analytics Production/Operations Management Concepts Production/Operations Management Concepts Operations Strategy Operations Strategy Supply Chain Management Supply Chain Management Just-in-Time (JIT) Theory Just-in-Time (JIT) Theory MRP, ERP MRP, ERP ANOVA Model Correlation Analysis Multiple Regression Model Time-Series Analysis 1 - Forecasting Model P/OM Intermediate Biz. Statistics Management Science/ Operations Research: Management Science/ Operations Research: Linear Programming Model Linear Programming Model Transportation Model Transportation Model Inventory Control Model Inventory Control Model Decision Tree Model Decision Tree Model Project Management – PERT/CPM Model Project Management – PERT/CPM Model TQM – Statistical Process Control Model Queuing Model Queuing Model Risk Management - System Reliability Model Risk Management - System Reliability Model MS/OR

Business Analytics 5 – MGMT 471, Advanced Business Analytics Structural Equation Modeling (SEM) Factor Analysis Discriminant Model Non-parametric Model Time-Series Analysis 2 – Advanced Forecasting Model Advanced Biz. Statistics LP Model 2 LP Model 2 Data Envelopment Analysis (DEA) Model Data Envelopment Analysis (DEA) Model Simulation Model Simulation Model Goal Programming (GP) Model Goal Programming (GP) Model Analytic Hierarchy Process (AHP) Model Analytic Hierarchy Process (AHP) Model Non-LP Model Non-LP Model Advanced MS/OR

Thank You! Any Questions? For More Information, contact: –Professor C. Christopher Lee, Ph.D: » or »Office - Library 319 »Phone: (906)