Experiments and Modeling in Cognitive Science

MATLAB, SPSS, Excel and E-Prime

Fabien Mathy, Mustapha Chekaf

• Publisher: ISTE Press - Elsevier
• Year: 2018
• Print ISBN: 9781785482847
• eBook ISBN: 9780081027974
• Topic: Psychology
• Subtopic: Cognitive Neuroscience & Neuropsychology
• Index: Psychology

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.- Covers the entire process of experimenting, from designing an experiment, to modeling the data- Shows how software can help automate various stages of the experiment for which operations may quickly become repetitive- Contains sections on how to compile data files (instead of opening files one by one to copy and paste) and generate stimuli (instead of drawing one by one in a drawing software)

Part 1

Experiments, Models, Simulations

1

Principles of Modeling*

Abstract

Cognitive sciences comprise a diverse group of disciplines working together with the goal of understanding how human knowledge is possible. This field uses the following four fundamental methods: conceptualization, experimentation, modeling and simulation, the latter of which is most characterized by the rise of informatics. In this chapter, we describe each of these methods, with a focus on modeling.

Keywords

Bifurcation; Conceptualization; Eratosthenes; Golden number; Hypothesis; Modeling; Parastichies; Reproduction; Simulations

Cognitive sciences comprise a diverse group of disciplines working together with the goal of understanding how human knowledge is possible. This field uses the following four fundamental methods: conceptualization, experimentation, modeling and simulation, the latter of which is most characterized by the rise of informatics. In this chapter, we describe each of these methods, with a focus on modeling.

1.1 Experiments, models and simulations

Starting with the most essential method, experimentation involves manipulating one or several factors with the goal of measuring their effects. Experimentation is usually the result of a process of conceptualization that allows a question to be asked and a hypothesis to be provided as the answer to this question. The answer to the question is a prediction of an effect. For example, if we assume that Sunlight is needed for the growth of plants, then we might ask what happens if we try to grow plants in the dark, and a simple hypothesis might be that the plant would die in the dark. In order to avoid circumstances that are unfavorable (such as experimenting on a sick plant) or favorable to the objectives of the experiment (such as choosing a particularly robust plant), it is best to choose several different plants, placed in the dark for a month, and to compare their growth with that of another set of plants, placed in the light of day, while making sure that factors like the temperature of the two areas are the same. Making sure that the two conditions are treated equally allows the experimenter to manipulate the experimental factor “all other things being equal” (“ceteris paribus”), which ensures that the only difference that exists between the two sets of plants is due to the light factor. When a prediction is limited to a single experiment, it can be said that the hypothesis has been operationalized. There can be several possible experiments available for one hypothesis. Experimentation assumes that the dependent variable (DV, also called “measure”) is a function of the independent variable (IV, or “factor”), a relation that can be written as DV = f(IV). A way of remembering this is that the dependent variable “depends” on (i.e. is a function of) the ...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Preface
• Part 1: Experiments, Models, Simulations
• Part 2: Experimentation
• Part 3: Analysis and Modeling
• References
• Index