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Applied Business Statistics A Training Program for BCBS Professor Ahmadi Office: UTC - Fletcher 400C Telephone: (423) 425-4410 E-mail: [email protected] Books: 1. 2. Essentials of Statistics for Business and Economics, Fourth Edition, by Anderson, Sweeney & Williams (Thomson South-Western Publishing), 2005. Workbook to accompany Anderson, Sweeney and Williams' Essentials of Statistics for Business and Economics, Fourth Edition, by Mohammad Ahmadi (Thomson South-Western Publishing), 2005. DESCRIPTION AND OBJECTIVES The science of data analysis is commonly called Statistics. Statistics and statistical analyses are fundamental tools for managerial decision-making. Statistical analysis provides many ways to deal with uncertainties and, hence, is useful both for descriptive and for inferential tasks. This course presents statistical concepts and their applications for managerial decision-making. Computer based statistical analyses and the application of the insights gained through such statistical analyses for developing effective business decisions will be integrated into every aspect of the course. Topics addressed include organizing and summarizing data, graphical and tabular presentation of data using spreadsheets, probability theory, sampling distributions, estimation techniques, hypothesis testing for one and more than one population, and regression and correlation analysis. Other objectives of the course include: Using computer technologies for problem solving. Analyzing data and converting data into useful information. Working in a group and becoming a contributing team member. ENTRY SKILLS Basic algebra, familiarity with basic spreadsheet capabilities/features such as entering and editing data, formatting cells and columns, developing formulas, copying formulas, absolute and relative addressing of cells in formulas, and formatting print pages and printing. EXIT SKILLS Familiarity with basic statistical concepts, sources of data, descriptive statistics, probability theory, Poisson, Binomial, and Normal distributions, sampling distributions, interval estimation and hypothesis testing, analysis of variance, and regression and correlation analyses, ability to develop and analyze various quantitative models, spreadsheet functions, setting up spreadsheet templates for statistical models, spreadsheet commands for statistical analysis, and creating various graphs. Applied Business Statistics Tentative Schedule May 17 Chapter 1 – Introduction Data and Statistics – Application in Business Descriptive and Inferential Statistics Scales of Measurement Sources of Data 19 Chapter 2 – Tabular and Graphical Presentations (Start Using Excel) Frequency Distribution and Histogram Various Single and Multiple Plots Chapter 3 – Descriptive Statistics – Measures of location and dispersion Mean, Median, Mode, Percentiles, Quartiles Range, Variance, Standard Deviation, Coefficient of Variation Coefficient of Correlation Chapters 4 and 5 – Probability and probability distributions Basics Concepts of Probability Laws of Probability Discrete Probability Distributions (Binomial and Poisson) Chapters 6 – Continuous Probability Distributions Uniform Probability Distribution Normal Probability Distribution Chapter 7 – Sampling and Sampling Distribution Introduction to Sampling Distributions Sampling Distribution – Means Sampling Distribution – Proportions Sampling Methods Chapter 8 – Interval Estimation Means Proportions Sample Size Estimation Chapter 9 – Hypothesis Testing Developing Null and Alternative Hypotheses Type I and Type II Errors Hypothesis Test – Means Hypothesis Test - Proportions Chapter 10 – Comparisons Involving Means Inferences About the Difference between Two Population Means Matched (Pair) Samples Analysis of Variance (k Population Means) 24 26 31 June 2 7 9 14 2 16 21 23 28 30 Chapter 11 – Comparisons Involving Proportions Interval Estimation – Two Proportions Hypothesis Testing – Two Proportions Test of Goodness of Fit Test of Independence Chapters 12 – Simple Linear Regression and Correlation Least Square Method Coefficient of Determination Testing for Significance Prediction Chapters 13 – Multiple Regression Model Assumptions t-Tests F- Test Using Qualitative Independent Variables Forecasting Moving Averages Exponential smoothing Time Series Analysis Survey Design Focus Group Questionnaire Design Scaling Validity Reliability 3