05679oam 2200733 450 991045369840332120210113180205.01-118-65214-21-118-65224-X(CKB)2550000001165645(EBL)1563061(OCoLC)864916826(SSID)ssj0001059680(PQKBManifestationID)11634075(PQKBTitleCode)TC0001059680(PQKBWorkID)11084621(PQKB)11214170(DLC) 2013030468(JP-MeL)3000065444(MiAaPQ)EBC1563061(EXLCZ)99255000000116564520130729h20132014 uy 0engur|n|---|||||txtccrExplaining psychological statistics /Barry H. Cohen, New York University4th ed.Hoboken, NJ :John Wiley & Sons,2013.©20141 online resource (850 p.)CoursesmartDescription based upon print version of record.1-118-43660-1 1-306-15662-9 Includes bibliographical references and index.Cover; Title Page; Copyright; Contents; Key Formulas; Key Formulas; Preface to the Fourth Edition; Acknowledgments; Part One Descriptive Statistics; Chapter 1 Introduction to Psychological Statistics; A. Conceptual Foundation; What Is (Are) Statistics?; Statistics and Research; Variables and Constants; Scales of Measurement; Parametric Versus Nonparametric Statistics; Likert Scales and the Measurement Controversy; Continuous Versus Discrete Variables; Scales Versus Variables Versus Underlying Constructs; Independent Versus Dependent Variables; Experimental Versus Observational ResearchPopulations Versus SamplesStatistical Formulas; Summary; Exercises; B. Basic Statistical Procedures; Variables With Subscripts; The Summation Sign; Properties of the Summation Sign; Rounding Off Numbers; Summary; Exercises; C. Analysis by SPSS; Ihno's Data; Variable View; Data Coding; Missing Values; Computing New Variables; Reading Excel Files Into SPSS; Exercises; Chapter 2 Frequency Tables, Graphs, and Distributions; A. Conceptual Foundation; Frequency Distributions; The Cumulative Frequency Distribution; The Relative Frequency and Cumulative Relative Frequency DistributionsThe Cumulative Percentage DistributionPercentiles; Graphs; Real Versus Theoretical Distributions; Summary; Exercises; B. Basic Statistical Procedures; Grouped Frequency Distributions; Apparent Versus Real Limits; Constructing Class Intervals; Choosing the Class Interval Width; Choosing the Limits of the Lowest Interval; Relative and Cumulative Frequency Distributions; Cumulative Percentage Distribution; Estimating Percentiles and Percentile Ranks by Linear Interpolation; Graphing a Grouped Frequency Distribution; Guidelines for Drawing Graphs of Frequency Distributions; Summary; ExercisesC. Analysis by SPSSCreating Frequency Distributions; Percentile Ranks and Missing Values; Graphing Your Distribution; Obtaining Percentiles; The Split File Function; Stem-and-Leaf Plots; Exercises; Chapter 3 Measures of Central Tendency and Variability; A. Conceptual Foundation; Measures of Central Tendency; Measures of Variability; Skewed Distributions; Summary; Exercises; B. Basic Statistical Procedures; Formulas for the Mean; Computational Formulas for the Variance and Standard Deviation; Obtaining the Standard Deviation Directly From Your Calculator; Properties of the MeanProperties of the Standard DeviationMeasuring Skewness; Measuring Kurtosis; Summary; Exercises; C. Analysis by SPSS; Summary Statistics; Using Explore to Obtain Additional Statistics; Boxplots; Selecting Cases; Exercises; Key Formulas; Chapter 4 Standardized Scores and the Normal Distribution; A. Conceptual Foundation; z Scores; Finding a Raw Score From a z Score; Sets of z Scores; Properties of z Scores; SAT, T, and IQ Scores; The Normal Distribution; Introducing Probability: Smooth Distributions Versus Discrete Events; Real Distributions Versus the Normal Distributionz Scores as a Research Tool"Now in its 4th edition, this popular and comprehensive graduate-level statistics text offers students an easy to grasp and non-intimidating approach to statistics for the non-mathematician. The text provides practical coverage of SPSS in every chapter, including screen shots, procedures, exercises, and direction on how to interpret SPSS output. The use of common data sets throughout the book aid in student comprehension. Now with a new chapter showing students how to apply the right test in the right way to come out with the most accurate and true result, the new edition continues to offer students a lively and engaging introduction to the field"--Provided by publisher.PsychometricsPsychologyMathematical modelsStatisticsStudy and teaching (Higher)PSYCHOLOGY / StatisticsbisacshElectronic books.Psychometrics.PsychologyMathematical models.StatisticsStudy and teaching (Higher)PSYCHOLOGY / Statistics.150.1150/.1/5195PSY032000bisacshCohen Barry H.1949-515094DLCDLCDLCBOOK9910453698403321Explaining psychological statistics1994623UNINA04209nam 22008535 450 99620252560331620200701160604.03-319-11331-310.1007/978-3-319-11331-9(CKB)3710000000228648(SSID)ssj0001354086(PQKBManifestationID)11768666(PQKBTitleCode)TC0001354086(PQKBWorkID)11316852(PQKB)10120142(DE-He213)978-3-319-11331-9(MiAaPQ)EBC6303050(MiAaPQ)EBC5586991(Au-PeEL)EBL5586991(OCoLC)890805109(PPN)181351889(EXLCZ)99371000000022864820140902d2014 u| 0engurnn|008mamaatxtccrComputer Vision and Graphics[electronic resource] International Conference, ICCVG 2014, Warsaw, Poland, September 15-17, 2014, Proceedings /edited by Leszek J. Chmielewski, Ryszard Kozera, Bok-Suk Shin, Konrad Wojciechowski1st ed. 2014.Cham :Springer International Publishing :Imprint: Springer,2014.1 online resource (XV, 691 p. 382 illus.) Image Processing, Computer Vision, Pattern Recognition, and Graphics ;8671Includes index.3-319-11330-5 Combined metrics for color image quality assessment -- Quartic orders and sharpness -- Parallel simulation -- Mandelbrot- and Julia-like rendering -- Time compensation in perceptual experiments -- Fur visualization for computer game engines -- Multiple scattering in cumulus clouds -- Component weight tuning of SSIM image quality assessment measure.This book constitutes the refereed proceedings of the International Conference on Computer Vision and Graphics, ICCVG 2014, held in Warsaw, Poland, in September 2014. The 81 full papers presented were carefully reviewed and selected from various submissions. They cover various important aspects of computer vision and graphics.Image Processing, Computer Vision, Pattern Recognition, and Graphics ;8671Artificial intelligenceOptical data processingPattern recognitionAlgorithmsComputer graphicsApplication softwareArtificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Image Processing and Computer Visionhttps://scigraph.springernature.com/ontologies/product-market-codes/I22021Pattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XAlgorithm Analysis and Problem Complexityhttps://scigraph.springernature.com/ontologies/product-market-codes/I16021Computer Graphicshttps://scigraph.springernature.com/ontologies/product-market-codes/I22013Information Systems Applications (incl. Internet)https://scigraph.springernature.com/ontologies/product-market-codes/I18040Artificial intelligence.Optical data processing.Pattern recognition.Algorithms.Computer graphics.Application software.Artificial Intelligence.Image Processing and Computer Vision.Pattern Recognition.Algorithm Analysis and Problem Complexity.Computer Graphics.Information Systems Applications (incl. Internet).006.37Chmielewski Leszek Jedthttp://id.loc.gov/vocabulary/relators/edtKozera Ryszardedthttp://id.loc.gov/vocabulary/relators/edtShin Bok-Sukedthttp://id.loc.gov/vocabulary/relators/edtWojciechowski Konradedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK996202525603316Computer Vision and Graphics774196UNISA