Titlebook: Essentials of Business Analytics; An Introduction to t Bhimasankaram Pochiraju,Sridhar Seshadri Textbook 2019 Springer Nature Switzerland A

贪污

书目名称Essentials of Business Analytics影响因子(影响力)




书目名称Essentials of Business Analytics影响因子(影响力)学科排名




书目名称Essentials of Business Analytics网络公开度




书目名称Essentials of Business Analytics网络公开度学科排名




书目名称Essentials of Business Analytics被引频次




书目名称Essentials of Business Analytics被引频次学科排名




书目名称Essentials of Business Analytics年度引用




书目名称Essentials of Business Analytics年度引用学科排名




书目名称Essentials of Business Analytics读者反馈




书目名称Essentials of Business Analytics读者反馈学科排名

笨拙的我

Data Collectionf the characteristics of the data in question. How do we collect data? What kinds of data exist? Where is it coming from? Before beginning to analyze data, analysts must know how to answer these questions. In doing so, we build the base upon which the rest of our examination follows. This chapter ai

争论

Data Management—Relational Database Systems (RDBMS)at can be stored and processed by computers. In order to process and manipulate data efficiently, it is very important that data is stored in an appropriate form. Data comes in many shapes and forms, and some of the most commonly known forms of data are numbers, text, images, and videos. Depending o

RODE

FOLLY

HACK

Statistical Methods: Basic Inferencesrder to do this, we must be able to summarize and lay out datasets in a manner that allows us to use more advanced methods of examination. This chapter introduces fundamental methods of statistics, such as the central limit theorem, confidence intervals, hypothesis testing and analysis of variance (

HACK

Statistical Methods: Regression Analysis systematically develop linear regression modeling of data. Chapter 6 on Basic inference is all the prerequisite that is required for this chapter. We start with motivating examples (Sect. 2). Section 3 deals with the methods and diagnostics for linear regression. We start with a discussion on what

窝转脊椎动物

Text Analyticserstanding and examining data in word formats, which tend to be more unstructured and therefore more complex. Text analytics uses tools such as those embedded in R in order to extract meaning from large amounts of word-based data. Two methods are described in this chapter: bag-of-words and natural l

背叛者

Simulationg. Our focus will be on applications and to understand the steps in building a simulation model and interpreting the results of the model; the theoretical background can be found in the reference textbooks described at the end of the chapter. Simulation is a practical approach to decision making und

珊瑚