Data Analysis for Business Decision Making: A Laboratory Manual, Second Edition
- 1h 23m
- Andres Fortino
- Mercury Learning
- 2020
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 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 solution spreadsheets, sample files, data sets, etc. used in the book's case studies
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.
In this Book
-
Shaping and Cleaning Data
-
Installing the Analysis Toolpak
-
Descriptive Statistics
-
Histograms
-
Pare to Analysis
-
Scatter Plots
-
Correlation and Linear Regression
-
Multivariate Regression
-
Forecasting and Time Series
-
Inferential Statistics
-
Contingency Analysis
-
A/B Testing
-
Text Analytics
-
Analyzing Big Data Sets
-
Data Visualization
-
Summary of Analysis Techniques
