LEADER 05479nam 2200721 450 001 9910819245003321 005 20230601080222.0 010 $a1-118-60147-5 010 $a1-299-13995-7 010 $a1-118-60142-4 010 $a1-118-60151-3 035 $a(CKB)2670000000327424 035 $a(EBL)1117281 035 $a(SSID)ssj0000822502 035 $a(PQKBManifestationID)11456271 035 $a(PQKBTitleCode)TC0000822502 035 $a(PQKBWorkID)10756996 035 $a(PQKB)11595316 035 $a(Au-PeEL)EBL1117281 035 $a(CaPaEBR)ebr10653876 035 $a(CaONFJC)MIL445245 035 $a(CaSebORM)9781118601518 035 $a(MiAaPQ)EBC1117281 035 $a(OCoLC)826659636 035 $a(EXLCZ)992670000000327424 100 $a20160223h20112011 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt 182 $cc 183 $acr 200 14$aThe semantic sphere 1 $ecomputation, cognition and information economy /$fPierre Le?vy 205 $a1st edition 210 1$aLondon, England ;$aHoboken, New Jersey :$cISTE :$cWiley,$d2011. 210 4$dİ2011 215 $a1 online resource (399 p.) 225 1 $aISTE 300 $aDescription based upon print version of record. 311 1 $a1-84821-251-8 320 $aIncludes bibliographical references and index. 327 $aCover; Title Page; Copyright Page; Table of Contents; Acknowledgements; Chapter 1. General Introduction; 1.1. The vision: to enhance cognitive processes; 1.1.1. The semantic imperative; 1.1.2. The ethical imperative; 1.1.3. The technical imperative; 1.2. A transdisciplinary intellectual adventure; 1.2.1. The years of training, 1975-1992; 1.2.2. The years of conception 1992-2002; 1.2.3. The years of gestation, 2002-2010; 1.3. The result: toward hypercortical cognition; 1.3.1. A system of coordinates; 1.3.2. An information economy; 1.3.3. A Hypercortex to contribute to cognitive augmentation 327 $a1.4. General plan of this book PART 1. THE PHILOSOPHY OF INFORMATION; Chapter 2. The Nature of Information; 2.1. Orientation; 2.2. The information paradigm; 2.2.1. Information and symbolic systems; 2.2.2. The sources of the information paradigm; 2.2.3. Information between form and difference; 2.2.4. Information and time; 2.3. Layers of encoding; 2.3.1. A layered structure; 2.3.2. The physicochemical and organic layers; 2.3.3. The phenomenal layer; 2.3.4. The symbolic layer; 2.3.5. A synthetic view of the layers of information; 2.4. Evolution in information nature; 2.5. The unity of nature 327 $a2.5.1. Natural information and cultural information 2.5.2. Nature as a "great symbol"; Chapter 3. Symbolic Cognition; 3.1. Delimitation of the field of symbolic cognition; 3.1.1. Singularity; 3.1.2. Social and technical dimensions; 3.1.3. Symbolic manipulation goes far beyond linguistic competence and "reason"; 3.2. The secondary reflexivity of symbolic cognition; 3.2.1. The primary reflexivity of phenomenal consciousness; 3.2.2. The secondary reflexivity of discursive consciousness; 3.3. Symbolic power and its manifestations 327 $a3.4. The reciprocal enveloping of the phenomenal world and semantic world 3.5. The open intelligence of culture; 3.6. Differences between animal and human collective intelligence; Chapter 4. Creative Conversation; 4.1. Beyond "collective stupidity"; 4.2. Reflexive explication and sharing of knowledge; 4.2.1. Personal and social knowledge management; 4.2.2. The role of explication in social knowledge management; 4.2.3. Dialectic of memory and creative conversation; 4.3. The symbolic medium of creative conversation; 4.3.1. The question of the symbolic medium 327 $a4.3.2. The metalinguistic articulation of organized memory 4.3.3. How can creative conversation organize digital memory?; Chapter 5. Toward an Epistemological Transformation of the Human Sciences; 5.1. The stakes of human development; 5.1.1. The scope of human development; 5.1.2. In search of models of human development; 5.1.3. Social capital and human development; 5.1.4. The knowledge society and human development: a six-pole model; 5.2. Critique of the human sciences; 5.2.1. Human sciences and natural sciences; 5.2.2. Internal fragmentation; 5.2.3. Methodological weaknesses 327 $a5.2.4. Lack of coordination 330 $aThe new digital media offers us an unprecedented memory capacity, an ubiquitous communication channel and a growing computing power. How can we exploit this medium to augment our personal and social cognitive processes at the service of human development? Combining a deep knowledge of humanities and social sciences as well as a real familiarity with computer science issues, this book explains the collaborative construction of a global hypercortex coordinated by a computable metalanguage. By recognizing fully the symbolic and social nature of human cognition, we could transform our current 410 0$aISTE 606 $aComputer storage devices 606 $aDigital media 606 $aDigital media$xPsychological aspects 615 0$aComputer storage devices. 615 0$aDigital media. 615 0$aDigital media$xPsychological aspects. 676 $a004.5 700 $aLe?vy$b Pierre$f1956-$0382059 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910819245003321 996 $aThe semantic sphere 1$94009190 997 $aUNINA LEADER 05493nam 2200685 450 001 9910828437303321 005 20240102112643.0 010 $a0-19-939579-9 035 $a(CKB)2550000001302374 035 $a(EBL)1692209 035 $a(SSID)ssj0001194622 035 $a(PQKBManifestationID)12417546 035 $a(PQKBTitleCode)TC0001194622 035 $a(PQKBWorkID)11154073 035 $a(PQKB)11635318 035 $a(MiAaPQ)EBC1692209 035 $a(Au-PeEL)EBL1692209 035 $a(CaPaEBR)ebr10871675 035 $a(CaONFJC)MIL611015 035 $a(OCoLC)880147857 035 $a(EXLCZ)992550000001302374 100 $a20140526h20142014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStraightforward statistics $eunderstanding the tools of research /$fGlenn Geher and Sara Hall 210 1$aOxford :$cOxford University Press,$d[2014] 210 4$dİ2014 215 $a1 online resource (481 pages) 300 $aDescription based upon print version of record. 311 $a0-19-975176-5 311 $a1-306-79764-0 320 $aIncludes bibliographical references and index. 327 $aCover; Straightforward Statistics; Copyright; Contents; Preface; Acknowledgements; chapter 1 Prelude: Why Do I Need to Learn Statistics?; The Nature of Findings and Factsin the Behavioral Sciences; Statistical Significance and Effect Size; Descriptive and Inferential Statistics; A Conceptual Approach to Teachingand Learning Statistics; The Nature of this Book; How to Approach this Class andWhat You Should Get Out of It; Key Terms; chapter 2 Describing a Single Variable; Variables, Values, and Scores; Types of Variables; Describing Scores for a Single Variable; Indices of Central Tendency 327 $aIndices of Variability (and the SheerBeauty of Standard Deviation!)Rounding; Describing Frequencies of Valuesfor a Single Variable; Representing Frequency Data Graphically; Describing Data for a Categorical Variable; A Real Research Example; Summary; Key Terms; chapter 3 Standardized Scores; When a Z-Score Equals 0, the Raw ScoreIt Corresponds to Must Equal the Mean; Verbal Scores for the MadupistanAptitude Measure; Quantitative Scores for theMadupistan Aptitude Measure; Every Raw Score for Any VariableCorresponds to a Particular Z-Score 327 $aComputing Z-Scores for All Studentsfor the Madupistan Verbal TestComputing Raw Scores from Z-Scores; Comparing Your GPA of 3.10 from SolidState University with Pat's GPA of 1.95from Advanced Technical University; Each Z-Score for Any VariableCorresponds to a Particular Raw Score; Converting Z-Scores to Raw Scores(The Dorm Resident Example); A Real Research Example; Summary; Key Terms; chapter 4 Correlation; Correlations Are Summaries; Representing a Correlation Graphically; Representing a Correlation Mathematically; Return to Madupistan; Correlation Does Not Imply Causation 327 $aA Real Research ExampleSummary; Key Terms; chapter 5 Statistical Prediction and Regression; Standardized Regression; Predicting Scores on Y with DifferentAmounts of Information; Beta Weight; Unstandardized Regression Equation; The Regression Line; Quantitatively Estimating the PredictivePower of Your Regression Model; Interpreting r2; A Real Research Example; Conclusion; Key Terms; chapter 6 The Basic Elements of Hypothesis Testing; The Basic Elements ofInferential Statistics; The Normal Distribution; A Real Research Example; Summary; Key Terms; chapter 7 Introduction to Hypothesis Testing 327 $aThe Basic Rationale of Hypothesis TestingUnderstanding the BroaderPopulation of Interest; Population versus Sample Parameters; The Five Basic Steps of Hypothesis Testing; A Real Research Example; Summary; Key Terms; chapter 8 Hypothesis Testing if N > 1; The Distribution of Means; Steps in Hypothesis Testing if N > 1; Confidence Intervals; Real Research Example; Summary; Key Terms; chapter 9 Statistical Power; What Is Statistical Power?; An Example of Statistical Power; Factors that Affect Statistical Power; A Real Research Example; Summary; Key Terms 327 $achapter 10 t-tests (One-Sample and Within-Groups) 330 $aStraightforward Statistics: Understanding the Tools of Research is a clear and direct introduction to statistics for the social, behavioral, and life sciences. Based on the author's extensive experience teaching undergraduate statistics, this book provides a narrative presentation of the core principles that provide the foundation for modern-day statistics. With step-by-step guidance on the nuts and bolts of computing these statistics, the book includes detailed tutorials how to use state-of-the-art software, SPSS, to compute the basic statistics employed in modern academic and applied researc 606 $aPsychometrics 606 $aPsychology$xResearch 606 $aPsychology$xMathematical models 606 $aStatistics$xStudy and teaching (Higher) 615 0$aPsychometrics. 615 0$aPsychology$xResearch. 615 0$aPsychology$xMathematical models. 615 0$aStatistics$xStudy and teaching (Higher) 676 $a150.15195 700 $aGeher$b Glenn$01660717 702 $aHall$b Sara$f1979- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910828437303321 996 $aStraightforward statistics$94117725 997 $aUNINA