Ateneo - UPO

The course provides topics about: descriptive statistics, inferential statistics, methodology of research using statistical methods

Triola MM, Triola MF. Fondamenti di Statistica per le discipline biomediche, Pearson.
J.J. Shaughnessy, E.B. Zechmeister, J.S. Zechmeister. Metodologia della ricerca in psicologia. McGraw-Hill.

The course aims to: provide methodological issues related to descriptive and inferential statistics, select the appropriate statistical method to summarize study data, interpretation of the results, enable the student to participate in research in the social and socio-health area by knowing methods and tools.

Basic knowledge in mathematics

Lectures, Classroom exercises, Self-assessment test in Moodle-DIR

Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/services-students-physical-or-learning-disabilities Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination modalities, concerning academic aspects.

Written exam. The exam aims to verify knowledge and skills acquired by the student through the solution of exercises and open questions concerning the course programme

The frequency distribution
Measures of Central Tendency and dispersion
Properties of Probability
Probability distribution: the Binomial and normal distribution
Sampling distribution
Distribution of the sample mean
Confidence interval
Hypothesis testing: a single population mean, the difference between two population means.
Type I and type II error and the power of a test
Chi-square test

I - INTRODUCTORY PRINCIPLES TO SOCIAL STATISTICS AND THE METHODOLOGY OF RESEARCH: the use of descriptive statistics tools, the use of inferential statistics tools, the integration and applications of statistics to research in the social, socio-educational, socio-health fields, the need and meanings of a research methodology

II - RESEARCH TOOLS DESCRIBING AND ANALYZING QUANTITATIVE DATA: ORGANIZE YOUR DATA, KNOW THE DATA: Data cleaning, Frequency distribution, Graphical representation of data
DATA SYNTHESIS
CONFIRM WHAT THE DATA REVEALS.

III - RESEARCH TOOLS: OBSERVATION:
BEHAVIOR SAMPLING: Time sampling, Situation sampling
DIRECT OBSERVATION METHOD: Non-intrusive or naturalistic observation, Intrusive observation
INDIRECT OBSERVATION METHOD: Physical indicator, Archival documents
DOCUMENTATION OF BEHAVIOR: Comprehensive documentation of behavior, Selected records of behavior
ANALYSIS OF OBSERVATIONAL DATA: Qualitative data analysis, Quantitative data analysis
CRITICAL THINKING ABOUT OBSERVATIONAL RESEARCH: The influence of the observer, Observer bias

IV - RESEARCH TOOLS: THE SURVEY
USE OF THE INVESTIGATION, CHARACTERISTICS OF THE INVESTIGATION
SAMPLING IN THE INVESTIGATION: Basic terminology of sampling, Sampling procedures
INVESTIGATION METHOD: Postal questionnaires, Face-to-face interviews, Telephone interviews, Questionnaires via internet
RESEARCH DESIGNS FOR THE INVESTIGATION: Cross design, Trend study (independent longitudinal design), Longitudinal design
CONSTRUCTION OF THE QUESTIONNAIRE: The questionnaire tool, Create a questionnaire
CRITICAL APPROACH OF THE INVESTIGATION: Correspondence between described and real behavior, Correlation and causality

V - RESEARCH TOOLS: THE EXPERIMENT - INDEPENDENT GROUP DESIGN -
WHY DO EXPERIMENTS
THE LOGIC OF EXPERIMENTAL RESEARCH
RANDOM GROUPS DESIGN: An example of random group design, Randomized block design, Threats to internal validity
ANALYSIS AND INTERPRETATION OF EXPERIMENTAL RESULTS: Role of data analysis in experiments, Description of the results, Confirmation of results
EXTERNAL VALIDITY OF THE EXPERIMENTAL RESULTS

Knowledge and understanding: to go in depth of statistical methods for the analysis of clinical data and social statistics.
Ability to apply knowledge and understanding: translating theory into practice by concretely working at the solutions to exercises and using indicators in social and health contexts.
Decision-making autonomy: acquiring autonomy in decision to conduct the analysis of data obtained from surveys.
Communication skills: ability to communicate knowledge with clarity, scientific and methodological rigour.
Learning skills: dealing with the information obtained from clinical studies and social research with the objective of collecting and organizing data and correctly interpreting the information.