Cognitive neuroscience - Neuroscienze cognitive

Il corso tratterà i seguenti temi: uso dei motori di ricerca per ricerca bibliografica i tipi di paper e la metaanalisi validità degli studi sperimentali tipi di disegni sperimentali il single case formulazione di ipotesi dimensione del campione metodi di raccolta dati interpretazione dei risultati ed uso dei diversi grafici

Il corso è pensato per gli studenti che intendono approfondire le competenze sulle abilità di analisi dei dati I requisiti per frequentare il corso senza difficoltà sono: - conoscenza di base della psicometria - interesse per i metodi ed analisi della ricerca in neuroscienze cognitive

Agli studenti saranno fornite le slides discusse durante le lezioni Testi Manuale di statistica STATISTICA: at choice by the students METODOLOGIA E ANALISI DEI DATI: Metodologia della ricerca in psicologia Donald H. McBurney,Theresa L. White Editore: Il Mulino or Research Design in Clinical Psychology Alan E. Kazdin Pearson Education (US)

I temi saranno teoricamente presentati durante la lezione; gli esercizi saranno eseguiti durante le sessioni di laboratorio e riguarderanno diversi argomenti come i software statistici (SPSS, R) e Pubme

presenza ad oggi non sono previste lezioni in remoto questa condizione potrebbe subire dei cambiamenti qualora si rendesse necessario RECUPERARE delle ore di lezione

Lo scopo dell'esame finale è quello di testare l'apprendimento degli studenti sulle parti principali dei metodi sperimentali e degli studi sperimentali. L'esame finale metterà alla prova le capacità degli studenti di comprendere gli studi di ricerca Le domande riguarderanno sia le questioni teoriche che le applicazioni pratiche, la metodologia di analisi dei dati, i progetti statistici e le analisi statistiche nello specifico le domande d’esame verteranno sia su aspetti teorici presenti nei testi di riferimento, sia nell’interpretazione di risultati di specifici disegni sperimentali

I temi saranno teoricamente presentati durante la lezione; gli esercizi saranno eseguiti durante le sessioni di laboratorio e riguarderanno diversi argomenti come i software statistici (SPSS, R) e Pubme

The laboratory of DATA ANALYSIS AND STATISTICAL TESTING IN COGNITIVE NEUROSCIENCE deals with statistical methods for quantitative research in Psychology, using the software jamovi, and consists of four different teaching units. In the first part, basic descriptive statistics and measurement theory will be briefly recalled (students should be already familiar with them from previous basic courses). The second and the third part regards inferential statistics: basic concepts, univariate and multivariate data analyses. The fourth part concerns of relations among variables. The statistical software jamovi will be applied to illustrate those data analysis techniques. In particular, the topics that the laboratory will explore are the following. In the first part of the laboratory, we briefly recall descriptive statistics. The main topics are: Frequency distributions and tables; graphical representation of the data (e.g., histogram, bar-graph, chart-pie, line-graph ...); measures of central tendency (e.g., mode, median, mean); measures of dispersion (e.g., range, variance, standard deviation); positioning indexes (e.g., percentiles, quartiles, deciles ...); the normal curve; the standardized normal curve distribution; standardization of scores (e.g., z-scores, IQ deviation, T-scores ...). In the second part, we introduce inferential statistics and hypothesis testing. The main topics are: populations and samples; parameters and statistical indexes; different sampling techniques; the concept of probability; inferential statistics; parameters estimate: confidence intervals; hypothesis testing and statistical decision making; type error I and II; level of significance and p-value; statistical power and power analysis. In the third part, we deal on hypothesis testing on means. Hypothesis testing on two means: independent samples t-tests; Welch t-test for unequal variances groups; paired samples t-tests; one sample t-tests. Hypothesis testing on more than two means: models of Analysis of Variance (ANOVA). One-way ANOVA; factorial ANOVA; ANOVA with repeated measures; ANOVA for mixed designs (between and within factors); MANOVA; Analysis of Covariance. The fourth part will deal with the relationships between variables: bivariate correlation and linear regression. All statistical analyses will be explained and illustrated with practical exercises using the statistical software jamovi.

Basic mathematical competences provided at school will be necessary. A Psychometric course given during BA is to be preferable.

Theory: Howitt, D., & Cramer, D. (2011). Introduction to statistics in psychology (Fifth Edition). Edinburgh, UK: Pearson Education. (not-to-do chapt. 27, 29, 30, 32, 33, 35, 36, 38, 40, 41, 42) Jamovi: One of the following: a) Navarro DJ and Foxcroft DR (2022). learning statistics with jamovi: a tutorial for psychology students and other beginners. (Version 0.75). DOI: 10.24384/hgc3-7p15 (not-to-do chapt. 10, 16, 17) Available for free at: https://www.learnstatswithjamovi.com/ b) Richardson, P., & Machan, L. (2021). Jamovi for Psychologists. Bloomsbury Publishing. Other resourses will be avaliable on the eLearning page of the course. About jamovi: Jamovi is a freeware statistical software and can be downloaded at: https://www.jamovi.org/ User’s guide: https://www.jamovi.org/user-manual.html Getting started: https://docs.jamovi.org/

The course will be delivered in presence. Attending of the lessons is facultative but strongly encourages. Students who attend the course usually perform significantly better.

The exam consists of a written test, formed of closed-ended questions with close-ended answers. Each question has only one correct answer. One point is given for each correct answer, while zero points will be given to wrong answers. Therefore, no penalties is given to wrong answers. Questions are formulated in order to evaluate: a) the basic theoretical knowledge of the discipline; b) the skill to practically solve problems and exercises; c) the understanding of the processes involved in data analysis (e.g., hypothesis testing, statistical decision making); d) the critical reasoning skills (e.g., individuate and apply the correct statistical analysis in relation to a specific research question or problem); the expertise of reading statistical output and input of jamovi.

Vis-à-vis lessons are given to teach basic and theoretical concepts and knowledge. Practical exercise and activities, using the statistical software jamovi, are aimed to apply those concepts and knowledge. The course will be delivered in the classroom, no online neither blended lessons will be taken, unless if and when indicated by the authorities in relation to the health emergency. Both theoretical lessons and practical activities are aimed to learn and apply statistical knowledge with the software jamovi.