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Introduction to R for Business Intelligence

You're reading from   Introduction to R for Business Intelligence Profit optimization using data mining, data analysis, and Business Intelligence

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Product type Paperback
Published in Aug 2016
Publisher Packt
ISBN-13 9781785280252
Length 228 pages
Edition 1st Edition
Languages
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Author (1):
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Jay Gendron Jay Gendron
Author Profile Icon Jay Gendron
Jay Gendron
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Table of Contents (13) Chapters Close

Preface 1. Extract, Transform, and Load FREE CHAPTER 2. Data Cleaning 3. Exploratory Data Analysis 4. Linear Regression for Business 5. Data Mining with Cluster Analysis 6. Time Series Analysis 7. Visualizing the Datas Story 8. Web Dashboards with Shiny A. References
B. Other Helpful R Functions C. R Packages Used in the Book
D. R Code for Supporting Market Segment Business Case Calculations

Chapter 6. Time Series Analysis

Time series analysis is the most difficult analysis technique presented in this book. One may argue that it does not belong in an introductory book. It is true that this is a challenging topic. However, one may also argue that an introductory awareness of a difficult topic is better than perfect ignorance of it. Time series analysis is a technique designed to look at chronologically ordered data that may form cycles over time. Key topics covered in this chapter include the following:

  • Analyzing time series data with linear regression
  • Introducing key elements of time series analysis
  • Building ARIMA time series models

Time series analysis is an upper-level college statistics course. It is also a demanding topic taught in econometrics. This chapter provides you with an understanding of a useful but difficult analysis technique. It provides a combination of theoretical learning and hands-on practice. The goal is to provide you with a basic understanding of...

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