1 BUSINESS MANAGEMENT 2320 DECISION SCIENCES STATISTICAL TECHNIQUES Autumn 2014 INSTRUCTOR Mrs Bonnie Schroeder OFFICE Fisher Hall 330 FCOB ms2320ta osu edu all general course and concept questions schroeder 1 osu edu all questions concerns for which I alone would be able to grant a permission example make up exam or supply the information example course grade All communications must use secure OSU e mail Do not use gmail yahoo or other personal e E MAIL mail accounts SUBJECT heading required for all e mail communications BM2320 instructor name recitation day and time If protocol is followed you should expect a response no later than the next business day VOICE MAIL for emergency messages only 688 8062 TAs See Carmen AU14 BUSMGT 2320 Content Syllabus and General Information Office Hours are run according to a FIFS system You cannot schedule time during office hours for an appointment Come organized and prepared to ask questions Office hours are not for camping to do homework and or to study OFFICE HOURS All students are invited to utilize all office hours scheduled by all instructors and TAs An Excel file containing a complete schedule of office hours offered by all BM2320 instructors and TAs will be posted on Carmen AU14 BUSMGT 2320 Content Syllabus and General Information COURSE REQUIREMENTS PREREQUISITES Statistics 1430 and CSE 2111 or 1113 Note We are not able to waive prerequisites for this class Moore McCabe Alwan Craig Duckworth The Practice of Statistics for Business and Economics 3rd edition REQUIRED TEXT W H Freeman and Co Chapters 1 15 ISBN 10 1429242531 or 13 9781429242530 Chapter 15 is a supplemental chapter not printed with the standard text book It is however free and open at the companion web site for the text book see below Turning Technologies Clicker RF model is adequate CLASSROOM SUPPORT MATERIALS Calculator no requirements restrictions but one is required for every lecture recitation and exam Probability tables Carmen AU14 BUSMGT 2320 Content Probability Tables Course formula packet Carmen AU14 BUSMGT 2320 Content Formula Pages COMPANION WEB SITE FOR TEXT CARMEN http www whfreeman com psbe3e Data sets Applets Supplemental Chapters Chapter 15 etc http carmen osu edu General information Videos Lecture and Recitation materials Assignments Grades etc 2 COURSE OVERVIEW and OBJECTIVES A Vast amounts of data are collected in today s global business and economic environment The most successful decision makers and managers are those individuals groups that can put this information to work effectively to guide their decision process Accountants routinely conduct audits for their clients using statistical sampling procedures that allow them to draw a conclusion about the accuracy of the accounts receivable amount shown on a balance sheet based on the information obtained from the carefully validated sample Financial advisors use a variety of statistical information to measure the risk associated with investments A variety of statistical information is used in production processes to monitor the quality of the output of that process Electronic scanners used at retail checkout counters gather data used in establishing future marketing strategies These are but a few examples of the uses of information generated through statistical analysis of data The first objective of the course then is to familiarize you with some common statistical methods used for generating decision making information from data We will focus our attention on Classical methods for estimation and hypothesis testing Analysis of Variance Regression analysis and model building and forecasting with time series We emphasize data investigation and mastering statistical reasoning not mathematical rigor Our approach will generally follow a three step process 1 PLAN Identify the question that needs to be answered Obtain relevant data Understand the characteristics of the data Select a model and method The Normal and Binomial models will be stressed because of their general applicability and ease of implementation but they are applicable only under certain conditions Before any calculations are performed we must verify that the data conditions support the model 2 CALCULATE All formulas and calculations must be understood and therefore demonstrated and practiced in order to use the methods properly The computational burden will be eased in practice by the use of readily available statistical computer software 3 COMMUNICATE Proper selection of the model accurate measurement and a correct analysis are necessary but not sufficient for the solution of management problems The final and most important part is the interpretation of the results of the analysis We will emphasize contextual communication of the results of a statistical analysis to a business audience B Professional appearance and conduct effective communication self motivation and team work are as vital for ensuring success in the business environment as are strong technical skills Inattentiveness during meetings talking or text messaging while others are speaking and arriving late to appointments are unacceptable behaviors in the business arena Preparing incomplete unorganized sloppy and or illegible projects will limit your promotion possibilities Missing project deadlines will compromise your employment status A secondary goal of the course then will be development of behaviors work habits and communication skills consistent with expectations in the business environment To that end we have some classroom rules and class participation points can be deducted for violation of these rules 1 Common courtesy will be extended to everyone peers and instructors 2 Use of electronic devices is restricted to class related activities 3 Late arrivals and or early departures are frowned upon If you arrive late or must leave the room before class has been dismissed do not walk across the front of the room 4 Be prepared for every class meeting research the discussion topics and have appropriate materials 5 Sleeping during class is strictly prohibited 3 PROCEDURES Instruction Practice Graded Evaluation A Instruction We will employ three instructional components all of which are equally essential to your success in understanding the course material Each week is comprised of 1 Recitation weekly small meeting with an experienced instructor In general the previous week s material will be reinforced and practiced New concept may be introduced on occasion Recitation Practice