Parsing Psychology Statistical And Computational Methods Using Physiological Behavioral Social And Cognitive Data
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Parsing Psychology: Statistical and Computational Methods using Physiological, Behavioral, Social, and Cognitive Data
Author: Pietro Cipresso
language: en
Publisher: Frontiers Media SA
Release Date: 2020-02-14
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Computer-Aided Numerical Methods in Psychology
Author: PressGrup Academician Team
language: en
Publisher: Prof. Dr. Bilal Semih Bozdemir
Release Date:
Psychology: Computer-Aided Numerical Methods Introduction to Numerical Methods in Psychology Advantages of Computer-Aided Numerical Analysis Data Collection and Preprocessing Linear Regression and Correlation Analysis Logistic Regression and Classification Principal Component Analysis (PCA) Cluster Analysis Time Series Analysis Bayesian Methods and Inference Monte Carlo Simulation Techniques Optimization Algorithms in Psychological Research Visualization and Interpretation of Results Practical Applications and Case Studies
Statistics for Psychology II
Author: PressGrup Academician Team
language: en
Publisher: Prof. Dr. Bilal Semih Bozdemir
Release Date:
Interpreting and Reporting Statistical Results In the realm of psychological research, the ability to interpret and report statistical results accurately is paramount. This chapter delves into the essential guidelines and practices that researchers must follow to communicate findings effectively and responsibly. As psychologists often work with complex data sets, the interpretation of statistical results demands clarity, precision, and rigor. Understanding Statistical Output The first step in interpreting statistical results is to comprehend the output generated by statistical software. This output typically includes a range of statistics such as p-values, confidence intervals, regression coefficients, and others, depending on the analysis conducted. Each of these elements conveys critical information, which must be accurately interpreted to draw meaningful conclusions. For example, in hypothesis testing, the p-value indicates the probability of obtaining results as extreme as observed, assuming the null hypothesis is true. A p-value less than the predefined alpha level (commonly set at 0.05) leads to the rejection of the null hypothesis. Researchers must not only report the p-value but also contextualize it within the broader framework of the study, including the sample size and effect size.