E-Book, Englisch, 219 Seiten, eBook
Tripathi Learn Business Analytics in Six Steps Using SAS and R
1. Auflage 2016
ISBN: 978-1-4842-1001-7
Verlag: APRESS
Format: PDF
Kopierschutz: 1 - PDF Watermark
A Practical, Step-by-Step Guide to Learning Business Analytics
E-Book, Englisch, 219 Seiten, eBook
ISBN: 978-1-4842-1001-7
Verlag: APRESS
Format: PDF
Kopierschutz: 1 - PDF Watermark
Apply analytics to business problems using two very popular software tools, SAS and R. No matter your industry, this book will provide you with the knowledge and insights you and your business partners need to make better decisions faster.
teaches you how to solve problems and execute projects through the "DCOVA and I" (Define, Collect, Organize, Visualize, Analyze, and Insights) process. You no longer need to choose between the two most popular software tools. This book puts the best of both worlds—SAS and R—at your fingertips to solve a myriad of problems, whether relating to data science, finance, web usage, product development, or any other business discipline.
What You'll Learn
- Use the DCOVA and I process: Define, Collect, Organize, Visualize, Analyze and Insights.
- Harness both SAS and R, the star analytics technologies in the industry
- Use various tools to solve significant business challenges
- Understand how the tools relate to business analytics
- See seven case studies for hands-on practice
This book is for all IT professionals, especially data analysts, as well as anyone who
- Likes to solve business problems and is good with logical thinking and numbers
- Wants to enter the analytics world and is looking for a structured book to reach that goal
- Is currently working on SAS , R, or any other analytics software and strives to use its full power
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Weitere Infos & Material
Chapter Description and Details1 The Process of Analytics: DCOVA and I 1.1 What is analytics?1.2 The process of Analytics 1.2.1 Define 1.2.2 Collect1.2.3 Organize1.2.4 Visualize1.2.5 Analyze1.2.6 Insight 2 Accessing SAS and R 2.1 Why SAS and R2.2 History of SAS and R2.3 Installing SAS and R3 Data Manipulation using SAS and R: Collecting and Organizing the Data 3.1 Data flow from ERP to Business Analytics SaaS3.2 Sanity check on data 3.3 Merging datasets 3.4 Missing values, Duplication , Outliers 3.5 Project datamart4 Discover basic information about data 4.1 Descriptive statistics , measures of central tendency, measures of variation 4.2 How to generate them using:4.2.1 SAS4.2.2 R5 Visualisation 5.1 Graphs and charts5.2 How to create effective graphs and charts using:5.2.1 SAS5.2.2 R5.3 Correlation and co-variance5.4 How to create graphical and numeric outputs for correlation and co-variance using 5.4.1 SAS5.4.2 R6 Analyze: Probability and Distributions 6.1 Concepts of probability 6.2 How to generate probability using:6.2.1 SAS6.2.2 R6.3 Concepts of distributions6.4 Normal distributions6.5 How to work on distributions using:6.5.1 SAS6.5.2 R7 Analyze: Sampling and Sampling Distributions 7.1 Sampling and sampling distributions 7.2 Hypothesis testing 7.3 How to work on sampling and hypothesis testing using:7.3.1 SAS7.3.2 R8 Analyze: Confidence Interval8.1 Concept of confidence interval8.2 How to work in confidence intervals using8.2.1 SAS8.2.2 R9 Insight Generation9.1 What type of conclusions can be drawn by the analysis9.2 Interpreting results generated by:9.2.1 SAS9.2.2 R




