bayes4psy
ǂan ǂopen source R package for Bayesian statistics in psychology
Povzetek
Research in psychology generates complex data and often requires unique statistical analyses. These tasks are often very specific, so appropriate statistical models and methods cannot be found in accessible Bayesian tools. As a result, the use of Bayesian methods is limited to researchers and students that have the technical and statistical fundamentals that are required for probabilistic programming. Such knowledge is not part of the typical psychology curriculum and is a difficult obstacle for psychology students and researchers to overcome. The goal of the bayes4psy package is to bridge this gap and offer a collection of models and methods to be used for analysing data that arises from psychological experiments and as a teaching tool for Bayesian statistics in psychology. The package contains the Bayesian t-test and bootstrapping along with models for analysing reaction times, success rates, and tasks utilizing colors as a response. It also provides the diagnostic, analytic and visualization tools for the modern Bayesian data analysis workflow.
Ključne besede
psihologija;statistika;statistične analize;Bayesova analiza;obdelava podatkov;računalniški programi;R;psychology;statistics;statistical analysis;Bayesian analysis;data analysis;computer software;
Podatki
| Jezik: | Angleški jezik |
|---|---|
| Leto izida: | 2020 |
| Tipologija: | 1.01 - Izvirni znanstveni članek |
| Organizacija: | UL FRI - Fakulteta za računalništvo in informatiko |
| UDK: | 159.9.075:[311:004.4R] |
| COBISS: |
14800387
|
| ISSN: | 1664-1078 |
| Št. ogledov: | 441 |
| Št. prenosov: | 144 |
| Ocena: | 0 (0 glasov) |
| Metapodatki: |
|
Ostali podatki
| Sekundarni jezik: | Slovenski jezik |
|---|---|
| Sekundarne ključne besede: | Bayesova statistika;R;psihologija;reakcijski čas;uspešnost;Bayesov t-test;analiza barv;linearni model; |
| Vrsta dela (COBISS): | Članek v reviji |
| Strani: | str. 1-20 |
| Letnik: | ǂVol. ǂ11 |
| Zvezek: | ǂart. ǂ947 |
| Čas izdaje: | May 2020 |
| DOI: | 10.3389/fpsyg.2020.00947 |
| ID: | 12907173 |
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