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001 EBC4772359
003 MiAaPQ
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006 m o d |
007 cr cnu||||||||
008 240724s2016 xx o ||||0 eng d
020 _a9781484210017
_q(electronic bk.)
020 _z9781484210024
035 _a(MiAaPQ)EBC4772359
035 _a(Au-PeEL)EBL4772359
035 _a(CaPaEBR)ebr11319762
035 _a(CaONFJC)MIL984432
035 _a(OCoLC)967546628
040 _aMiAaPQ
_beng
_erda
_epn
_cMiAaPQ
_dMiAaPQ
050 4 _aQA76.9.B45
100 1 _aTripathi, Subhashini Sharma.
245 1 0 _aLearn Business Analytics in Six Steps Using SAS and R :
_bA Practical, Step-By-Step Guide to Learning Business Analytics.
250 _a1st ed.
264 1 _aBerkeley, CA :
_bApress L. P.,
_c2016.
264 4 _c©2016.
300 _a1 online resource (226 pages)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
505 0 _aIntro -- Contents at a Glance -- Contents -- About the Author -- Acknowledgments -- Introduction -- Chapter 1: The Process of Analytics -- What Is Analytics? What Does a Data Analyst Do? -- An Example -- A Typical Day -- Is Analytics for You? -- Evolution of Analytics: How Did Analytics Start? -- The Quality Movement -- The Second World War -- Where Else Was Statistics Involved? -- The Dawn of Business Intelligence -- Chapter 2: Accessing SAS and R -- Why SAS and R? -- Market Overview -- What Is Advanced Analytics? -- History of SAS and R -- History of SAS -- What Is EG? -- How Can You Access SAS Enterprise Guide Software? -- History of R -- Why Was R Named R? -- What Is R? -- What Is RStudio? -- What Is CRAN? -- Which Add-on Packages Exist for R? -- Why Is Microsoft's Acquisition of Revolution Analytics Important? -- Installing SAS and R -- Installing SAS -- SAS University Edition -- SAS OnDemand for Academics -- Education Analytical Suite -- Installing R -- Chapter 3: Data Manipulation Using SAS and R -- Define: The Phase Before Data Manipulation (Collect and Organize) -- Basic Understanding of Common Business Problems -- Sources of Data -- The Use of Benchmarks to Create an Optimal Define Statement -- Data Flow from ERP to Business Analytics SaaS -- What Are Primary Keys? -- What Is a Relational Database? -- Sanity Check on Data -- Case Study 1 -- Case Study 1 with SAS -- Case Study 1 with R -- Chapter 4: Discover Basic Information About Data Using SAS and R -- What Are Descriptive Statistics? -- More About Inferential and Descriptive Statistics -- Tables and Descriptive Statistics -- What Is a Frequency Distribution? -- Case Study 2 -- Solving Case Study 2 with SAS -- The UNIVARIATE Procedure -- Solving Case Study 2 with R -- Using Descriptive Statistics -- Measures of Central Tendency -- What Is Variation in Statistics?.
505 8 _aAbsolute and Mean Absolute Deviation -- Variance -- Chapter 5: Visualization -- What Is Visualization? -- Data Visualization in Today's World -- Why Do Data Visualization? -- What Are the Common Types of Graphs and Charts? -- Case Study on Graphs and Charts Using SAS -- About the Data -- What Is This Data? -- Definitions -- Problem Statement -- Solution in SAS -- SAS Code and Solution -- Visualization -- Case Study on Graphs and Charts Using R -- About the Data -- What Is This Data? -- Definitions -- Problem Statement -- Solution in R -- R Code and Solution -- Visualization -- What Are Correlation and Covariance? -- How to Interpret Correlation -- Chapter 6: Probability Using SAS and R -- What Is Probability? -- Probability of Independent Events: The Probability of Two or More Events -- Probability of Conditional Events: The Probability of Two or More Events -- Why Use Probability? -- Bayes' Theorem to Calculate Probability -- Bayes' Theorem in Terms of Likelihood -- Derivation of Bayes' Theorem from Conditional Probabilities -- Decision Tree: Use It to Understand Bayes' Theorem -- Frequency to Calculate Probability -- For Discrete Variables -- For Continuous Variables -- Normal Distributions to Calculate Probability -- What If the Variable Is Not Normally Distributed? -- Case Study Using SAS -- Problem Statement -- Solution -- SAS Task to Do 1 -- SAS Task to Do 2 -- Case Study in R -- Problem Statement -- Solution -- R Task to Do -- Chapter 7: Samples and Sampling Distributions Using SAS and R -- Understanding Samples -- Sampling Distributions -- Discrete Uniform Distribution -- Binomial Distribution -- Continuous Uniform Distribution -- Possion Distribution -- Use of Probability Distributions -- Central Limit Theorem -- The Law of Large Numbers -- Parametric Tests -- Nonparametric Tests -- Case Study Using SAS -- Case Study Using R.
505 8 _aChapter 8: Confidence Intervals and Sanctity of Analysis Using SAS and R -- How Can You Determine the Statistical Outcome? -- What Is the P-value? -- Errors in Hypothesis Testing -- Case Study in SAS -- Case Study with R -- Chapter 9: Insight Generation -- Introducing Insight Generation -- Descriptive Statistics -- Graphs -- Inferential Statistics -- Differences Statistics -- Case Study with SAS -- Case Study in R -- Index.
588 _aDescription based on publisher supplied metadata and other sources.
590 _aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
650 0 _aBig data.
655 4 _aElectronic books.
776 0 8 _iPrint version:
_aTripathi, Subhashini Sharma
_tLearn Business Analytics in Six Steps Using SAS and R
_dBerkeley, CA : Apress L. P.,c2016
_z9781484210024
797 2 _aProQuest (Firm)
856 4 0 _uhttps://ebookcentral.proquest.com/lib/orpp/detail.action?docID=4772359
_zClick to View
999 _c121380
_d121380