Data Analysis for Business Decisions : : A Laboratory Manual / / Andres Fortino.

• VerfasserIn: Fortino, Andres,
• Place / Publishing House: Dulles, VA : : Mercury Learning and Information, , [2020]; ©2020
• Year of Publication: 2020
• Language: English
• Physical Description: 1 online resource (166 p.)
• Other title: Frontmatter --; Contents --; Preface --; Chapter 1 Shaping and Cleaning Data --; Chapter 2 Installing the Analysis ToolPak --; Chapter 3 Descriptive Statistics --; Chapter 4 Histograms --; Chapter 5 Pareto Analysis --; Chapter 6 Scatter Plots --; Chapter 7 Correlation and Linear Regression --; Chapter 8 Multivariate Regression --; Chapter 9 Forecasting and Time Series --; Chapter 10 Inferential Statistics --; Chapter 11 Contingency Analysis --; Chapter 12 A/B Testing --; Chapter 13 Text Analytics --; Chapter 14 Analyzing Big Data Sets --; Chapter 15 Data Visualization --; Chapter 16 Summary of Analysis Techniques --; Index
• Format: Mode of access: Internet via World Wide Web.
• ISBN: 9781683925903
• Access: restricted access
• Hierarchical level: Monograph
• Statement of Responsibility: Andres Fortino.

This laboratory manual is intended for business analysts who wish to increase their skills in the use of statistical analysis to support business decisions. Most of the case studies use Excel, today's most common analysis tool. They range from the most basic descriptive analytical techniques to more advanced techniques such as linear regression and forecasting. Advanced projects cover inferential statistics for continuous variables (t-Test) and categorical variables (chi-square), as well as A/B testing. The manual ends with techniques to deal with the analysis of text data and tools to manage the analysis of large data sets (Big Data) using Excel. Includes companion files with solution spreadsheets, sample files, data sets, etc. from the book. Features:Teaches the statistical analysis skills needed to support business decisionsProvides projects ranging from the most basic descriptive analytical techniques to more advanced techniques such as linear regression, forecasting, inferential statistics, and analyzing big data setsIncludes companion files with solution spreadsheets, sample files, data sets, etc. used in the book's case studiesThe companion files are available online by emailing the publisher with proof of purchase at [e-mail].