Statistics in psychology using R and SPSS

Media type: E-Book

Title: Statistics in psychology using R and SPSS

Contributor: Rasch, Dieter [Author]; Kubinger, Klaus D. [Other]; Yanagida, Takuya [Other]

imprint: Chichester, West Sussex, UK: John Wiley & Sons, 2011

Extent: 1 Online-Ressource (xi, 552 pages); illustrations

Language: English

DOI: 10.1002/9781119979630

ISBN: 1119979641; 1119952026; 9781119979647; 9781119952022

Identifier:

Keywords: SPSS (Computer file) ; Psychometrics ; Social sciences Statistical methods Computer programs ; Psychometrics methods ; Statistics as Topic methods ; Software ; Social sciences ; Statistical methods ; Computer programs ; Statistik ; Psychologie ; SPSS ; PSYCHOLOGY ; Research & Methodology ; Service des Sociétés Secrètes

Origination:

Footnote: Includes bibliographical references and index

Description: Statistics in Psychology covers all statistical methods needed in education and research in psychology. This book looks at research questions when planning data sampling, that is to design the intended study and to calculate the sample sizes in advance. In other words, no analysis applies if the minimum size is not determined in order to fulfill certain precision requirements. The book looks at the process of empirical research into the following seven stages: Formulation of the problem, Stipulation of the precision requirements, Selecting the statistical model for the planning and analysis, The (optimal) design of the experiment or survey, Performing the experiment or the survey, Statistical analysis of the observed results, Interpretation of the results

6.2.2 Normal Distribution -- 6.3 Quantiles of Theoretical Distribution Functions -- 6.4 Mean and Variance of Theoretical Distributions -- 6.5 Estimation of Unknown Parameters -- References -- 7 Assumptions -- Random Sampling and Randomization -- 7.1 Simple Random Sampling in Surveys -- 7.2 Principles of Random Sampling and Randomization -- 7.2.1 Sampling Methods -- 7.2.2 Experimental Designs -- References -- 8 One Sample from One Population -- 8.1 Introduction -- 8.2 The Parameter μ of a Character Modeled by a Normally Distributed Random Variable -- 8.2.1 Estimation of the Unknown Parameter μ -- 8.2.2 A Confidence Interval for the Unknown Parameter μ -- 8.2.3 Hypothesis Testing Concerning the Unknown Parameter μ -- 8.2.4 Test of a Hypothesis Regarding the Unknown Parameter μ in the Case of Primarily Mutually Assigned Observations -- 8.3 Planning a Study for Hypothesis Testing with Respect to μ -- 8.4 Sequential Tests for the Unknown Parameter μ -- 8.5 Estimation, Hypothesis Testing, Planning the Study, and Sequential Testing Concerning Other Parameters -- 8.5.1 The Unknown Parameter σ2 -- 8.5.2 The Unknown Parameter p of a Dichotomous Character -- 8.5.3 The Unknown Parameter p of a Dichotomous Character which is the Result of Paired Observations -- 8.5.4 The Unknown Parameter pj of a Multi-Categorical Character -- 8.5.5 Test of a Hypothesis about the Median of a Quantitative Character -- 8.5.6 Test of a Hypothesis about the Median of a Quantitative Character which is the Result of Paired Observations -- References -- 9 Two Samples from Two Populations -- 9.1 Hypothesis Testing, Study Planning, and Sequential Testing Regarding the Unknown Parameters μ1 and μ2 -- 9.2 Hypothesis Testing, Study Planning, and Sequential Testing for Other Parameters -- 9.2.1 The Unknown Location Parameters for a Rank-Scaled Character.

9.2.2 The Unknown Parameters σ2 1 and σ2 -- 9.2.3 The Unknown Parameters p1 and p2 of a Dichotomous Character -- 9.2.4 The Unknown Parameters pi of a Multi-Categorical Nominal-Scaled Character -- 9.3 Equivalence Testing -- References -- 10 Samples from More than Two Populations -- 10.1 The Various Problem Situations -- 10.2 Selection Procedures -- 10.3 Multiple Comparisons of Means -- 10.4 Analysis of Variance -- 10.4.1 One-Way Analysis of Variance -- 10.4.2 One-Way Analysis of Variance for Ordinal-Scaled Characters -- 10.4.3 Comparing More than Two Populations with Respect to a Nominal-Scaled Character -- 10.4.4 Two-Way Analysis of Variance -- 10.4.5 Two-Way Analysis of Variance for Ordinal-Scaled Characters -- 10.4.6 Bivariate Comparison of Two Nominal-Scaled Factors -- 10.4.7 Three-Way Analysis of Variance -- References -- Part IV DESCRIPTIVE AND INFERENTIAL STATISTICS FOR TWO CHARACTERS -- 11 Regression and Correlation -- 11.1 Introduction -- 11.2 Regression Model -- 11.3 Correlation Coefficients and Measures of Association -- 11.3.1 Linear Correlation in Quantitative Characters -- 11.3.2 Monotone Relation in Quantitative Characters and Relation between Ordinal-Scaled Characters -- 11.3.3 Relationship between a Quantitative or Ordinal-Scaled Character and a Dichotomous Character -- 11.3.4 Relationship between a Quantitative Character and a Multi-Categorical Character -- 11.3.5 Correlation between Two Nominal-Scaled Characters -- 11.3.6 Nonlinear Relationship in Quantitative Characters -- 11.4 Hypothesis Testing and Planning the Study Concerning Correlation Coefficients -- 11.5 Correlation Analysis in Two Samples -- References -- Part V INFERENTIAL STATISTICS FOR MORE THAN TWO CHARACTERS -- 12 One Sample from One Population -- 12.1 Association between Three or More Characters -- 12.1.1 Partial Correlation Coefficient.

Concept of the book -- Measuring in psychology -- Psychology : an empirical science -- Definition : character, chance, experiment, and survey -- Numerical and graphical data analysis -- Probability and distribution -- Assumptions : random sampling and randomization -- One sample from one population -- Two samples from two populations -- Samples from more than two populations -- Regression and correlation -- One sample from one population -- Samples from more than one population -- Model generation -- Theory-generating procedures.

12.1.2 Comparison of the Association of One Character with Each of Two Other Characters -- 12.1.3 Multiple Linear Regression -- 12.1.4 Intercorrelations -- 12.1.5 Canonical Correlation Coefficient -- 12.1.6 Log-Linear Models -- 12.2 Hypothesis Testing Concerning a Vector of Means μ -- 12.3 Comparisons of Means and 'Homological' Methods for Matched Observations -- 12.3.1 Hypothesis Testing Concerning Means -- 12.3.2 Hypothesis Testing Concerning the Position of Ordinal-Scaled Characters -- References -- 13 Samples from More than One Population -- 13.1 General Linear Model -- 13.2 Analysis of Covariance -- 13.3 Multivariate Analysis of Variance -- 13.4 Discriminant Analysis -- References -- Part VI MODEL GENERATION AND THEORY-GENERATING PROCEDURES -- 14 Model Generation -- 14.1 Theoretical Basics of Model Generation -- 14.1.1 Generalized Linear Model -- 14.1.2 Model with Latent Variables -- 14.2 Methods for Determining the Quality and Excellence of a Model -- 14.2.1 Goodness of Fit Tests -- 14.2.2 Coefficients of Goodness of Fit -- 14.2.3 Cross-Validation -- 14.3 Simulation -- Non-Analytical Solutions to Statistical Problems -- References -- 15 Theory-Generating Methods -- 15.1 Methods of Descriptive Statistics -- 15.1.1 Cluster Analysis -- 15.1.2 Factor Analysis -- 15.1.3 Path Analysis -- 15.2 Methods of Inferential Statistics -- 15.2.1 Further Analysis Methods for Classifying Research Units -- 15.2.2 Confirmatory Factor Analysis -- 15.2.3 Models of Item Response Theory -- References -- Appendix A: Data Input -- Appendix B: Tables -- Appendix C: Symbols and Notation -- References -- Index.

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