slide 1 DSCI 5180: Introduction to the Business Decision Process Spring 2013 – Dr. Nick Evangelopoulos Lecture 1: Introduction to 5180 class Review of Basic Statistics (Ch. 1-2)

slide 2 DSCI 5180 Decision Making Business Decision Making “Decisions, decisions, decisions… Eeny, meeny, miny, moe!” Miss Piggy, The Muppets (2011)

slide 3 DSCI 5180 Decision Making DSCI 5180 Learning Goals All business decisions require valid data and valid analytical techniques. The goals of this course include: G1. Developing an appreciation for the role of statistics in making decisions, G2. Reviewing the central concepts of statistical analysis, G3. Understanding Simple Regression/ Correlation as a data analysis technique, G4. Building models using Multiple Regression, G5. Understanding the role of ANOVA in experimental designs, and finally G6. Developing the capability to analyze data to enable better business decisions.

Introduction 4 Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc. Chapter 1 An Introduction to Regression Analysis Terry Dielman Applied Regression Analysis: A Second Course in Business and Economic Statistics, fourth edition

Introduction 5 Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc. A Mountain of Data  Advances in technology have buried present-day managers under a mountain of data.  This text has been prepared to give future managers some tools for examining relationships between two or more variables.  Some examples are how sales are affected by advertising, or what determines the selling price of a house.

Introduction 6 Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc. Regression Analysis  One of the most important tools for examining relationships between variables.  You develop an equation for predicting a dependent variable from one or more explanatory variables.  In the process, you also describe how the relationship operates and sometimes how to control the dependent variable.

Introduction 7 Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc. Trial and Error  Much statistical analysis is a multistage process of trial and error.  There is a good deal of exploratory work, then several stages of model building and judgment.  The emphasis of this text is on the process rather than computations or theory.

Introduction 8 Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc. Software  Three software packages are discussed in the text.  The first is Excel because it is so often used in business.  Minitab is an efficient standalone package that has been around since the 1970s.  SAS is an all-encompassing package that does many things other than statistical analysis.

Introduction 9 Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc. Data, Data, Data  Data sets for all the examples and exercises are on the CD.  They come in versions for all three packages.  Each chapter ends with a section illustrating how to apply the techniques with the software.  On these PowerPoint slides, almost all of the output is from Minitab.

slide 10 DSCI 5180 Decision Making HW 1 Warranty Calculation The average lifetime of tires produced at a tire factory is mu=50K miles. The standard deviation is 5K miles. If a 40K mile- warranty is offered to the consumers, what is the expected proportion of tires covered under the warranty? NOTE: This is suggested homework, aimed at helping you understand the course concepts and prepare for exams. DO NOT TURN IN.

slide 11 DSCI 5180 Decision Making The probability below Z = ( X -  )/  = (40 – 50)/5 = -10/5 = P(Z < -2.00) =