Software Simulation and Modeling in Psychology: MATLAB, SPSS, Excel and E-Prime describes all the stages of psychology experimentation, from the manipulation of factors, to statistical analysis, data modeling, and automated stimuli creation. The book shows how software can help automate various stages of the experiment for which operations may quickly become repetitive. For example, it shows how to compile data files (instead of opening files one by one to copy and paste), generate stimuli (instead of drawing one by one in a drawing software), and transform and recode tables of data.
This type of modeling in psychology helps determine if a model fits the data, and also demonstrates that the algorithmic is not only useful, but essential for modeling data.
1. 4: Introduction to Programming in MATLAB® - p. 65 2. Part 2: Experimentation - p. 95 3. 5: Principles of Experimentation Organization and Experimental Reasoning - p. 99 4. 6: Building Experimental Conditions from Random Draws or Permutations - p. 113 5. 7: Creating Stimuli Digitally - p. 131 6. 8: Experimenting with Psychtoolbox (and Others) - p. 157 7. Part 3: Analysis and Modeling - p. 195 8. 9: Analyzing Data: Import, Transformation, Compilation, Restructuring, Aggregation and Use of Statisticstoolbox - p. 199 9. 10: Introduction to Bayesian Analysis - p. 235 10. 11: Complex and Original Figures - p. 267 11. References - p. 281 12. Index - p. 287
Software Simulation and Modeling in Psychology: MATLAB, SPSS, Excel and E-Prime describes all the stages of psychology experimentation, from the manipulation of factors, to statistical analysis, data modeling, and automated stimuli creation. The book shows how software can help automate various stages of the experiment for which operations may quickly become repetitive. For example, it shows how to compile data files (instead of opening files one by one to copy and paste), generate stimuli (instead of drawing one by one in a drawing software), and transform and recode tables of data.
This type of modeling in psychology helps determine if a model fits the data, and also demonstrates that the algorithmic is not only useful, but essential for modeling data.
1. 4: Introduction to Programming in MATLAB® - p. 65 2. Part 2: Experimentation - p. 95 3. 5: Principles of Experimentation Organization and Experimental Reasoning - p. 99 4. 6: Building Experimental Conditions from Random Draws or Permutations - p. 113 5. 7: Creating Stimuli Digitally - p. 131 6. 8: Experimenting with Psychtoolbox (and Others) - p. 157 7. Part 3: Analysis and Modeling - p. 195 8. 9: Analyzing Data: Import, Transformation, Compilation, Restructuring, Aggregation and Use of Statisticstoolbox - p. 199 9. 10: Introduction to Bayesian Analysis - p. 235 10. 11: Complex and Original Figures - p. 267 11. References - p. 281 12. Index - p. 287
