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MERCURY LEARNING and INFORMATION provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets. We embrace both traditional and innovative publishing models designed to accommodate the needs of the intended audience by using the appropriate delivery methods.
Data Analysis For Business Decisions
A Laboratory Manual
Second Edition
ISBN: 9781683925927
Pub Date: August 2020
Specs: 7 x 9 Paperback
Pages: 166
Price: $49.95
This laboratory manual is intended for business analysts who wish to increase their skills in the use of data 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, and data visualization. Includes companion files with videos, solution spreadsheets, sample files, data sets, etc. from the book.
FEATURES
- Teaches the statistical analysis skills needed to support business decisions
- Provides projects ranging from the most basic descriptive analytical techniques to more advanced techniques such as linear regression, forecasting, inferential statistics, and analyzing big data sets
- Includes companion files with videos, solution spreadsheets, sample files, data sets, etc. used in the book's case studies
BRIEF TOC
1: Shaping and Cleaning Data. 2: Installing the Analysis ToolPak. 3: Descriptive Statistics. 4: Histograms. 5: Pareto Analysis. 6: Scatter Plots. 7: Correlation and Linear Regression. 8: Multivariate Regression. 9: Forecasting and Time Series. 10: Inferential Statistics. 11: Contingency Analysis. 12: A/B Testing. 13: Text Analytics. 14: Analyzing Big Data Sets. 15: Data Visualization. 16: Summary of Analysis Techniques. Index.
ABOUT THE AUTHOR
Andres Fortino, PhD holds an appointment as a clinical associate professor of management and systems at the NYU School of Professional Studies, where he teaches courses in business analytics, data mining, and data visualization. He also leads his own consulting company, Fortino Global Education. Dr. Fortino has published ten books and over 40 academic papers, and has received IBM's First Invention Level Award for his work in semiconductor research. He holds three US patents and ten invention disclosures.