http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Essentials of Excel, Excel VBA, SAS and Minitab for Statistical and Financial Analyses
XX, 1041 p. 906 illus., 781 illus. in color. online resource.
This introductory textbook for business statistics teaches statistical analysis and research methods via business case studies and financial data using Excel, MINITAB, and SAS. Every chapter in this textbook engages the reader with data of individual stock, stock indices, options, and futures. One studies and uses statistics to learn how to study, analyze, and understand a data set of particular interest. Some of the more popular statistical programs that have been developed to use statistical and computational methods to analyze data sets are SAS, SPSS, and MINITAB. Of those, we look at MINITAB and SAS in this textbook. One of the main reasons to use MINITAB is that it is the easiest to use among the popular statistical programs. We look at SAS because it is the leading statistical package used in industry. We also utilize the much less costly and ubiquitous Microsoft Excel to do statistical analysis, as the benefits of Excel have become widely recognized in the academic world and its analytical capabilities extend to about 90 percent of statistical analysis done in the business world. We demonstrate much of our statistical analysis using Excel and double check the analysis and outcomes using MINITAB and SAS – also helpful in some analytical methods not possible or practical to do in Excel. Excel 2013, MINITAB17, and SAS are integrated into the study and use of statistical analysis Programming – includes advanced applications of Excel (VBA – Visual Basic for Application) All Excel macros published for users to study Pedagogy from a business perspective – implementation of statistical concepts via case-study approach Each chapter uses data from individual stocks, stock indices, options, and futures A practical case-study based textbook for courses in business statistics, investment analysis, options, and futures An in-depth reference for statistical analysis using multiple software packages for financial industry professionals.
1 Introduction -- 2 Data Collection and Presentation -- 3 Histograms and the Rate of Returns of Johnson & Johnson -- 4 Numerical Summary Measures on Rate of Returns of Amazon, Walmart and the S&P 500 -- 5 Probability Concepts and Their Analysis -- 6 Discrete Random Variables and Probability Distributions -- 7 The Normal and Lognormal Distributions -- 8 Sampling Distributions and Central Limit Theorem -- 9 Other Continuous Distributions -- 10 Estimation -- 11 Hypothesis Testing -- 12 Analysis Of Variance and Chi-Square Tests -- 13 Simple Linear Regression and The Correlation Coefficient -- 14 Simple Linear Regression and Correlation: Analyses and Applications -- 15 Multiple Linear Regression -- 16 Residual and Regression Assumption Analysis -- 17 Nonparametric Statistics -- 18 Time-Series: Analysis, Model, and Forecasting -- 19 Index Numbers and Stock Market Indexes -- 20 Sampling Surveys: Methods and Applications -- 21 Statistical Decision Theory: Methods and Applications -- 22 Introduction to EXCEL Programming -- 23 Introduction to VBA Programming -- 24 Professional Techniques Used in EXCEL and EXCEL VBA Techniques. - 25 Binomial Option Pricing Model Decision Tree Approach -- 26 using Microsoft Excel to Estimate Alternative Option Pricing Models -- 27 Alternative Methods to Estimate Implied Variance -- 28 Greek Letters and Portfolio Insurance -- 29 Portfolio Analysis and Option Strategies -- 30 Simulation and its Application -- 31 Application of Simultaneous Equation in Finance Research: Methods and Empirical Results -- 32 Hedge Ratios: Theory and Applications.
by Cheng-Few Lee, John Lee, Jow-Ran Chang, Tzu Tai.
Statistics for Business/Economics/Mathematical Finance/Insurance
Statistics and Computing/Statistics Programs
Macroeconomics/Monetary Economics//Financial Economics