26259 - Applied Statistics

Learning outcomes

By the end of the course, students will know and understand the main research methods and data analysis applied to work and organizational psychology. In particular, students will be able to identify appropriate measures, to use statistical tools for data analysis, and to present results.

Course contents

Foundations: The research process and ethics in research. Research design. Types of designs and internal validity. Sampling: Size and representativeness. Cultural and contextual issues. External validity.

Choosing, adapting, and/or developing the measurement instruments: Types of measures in recruitment, selection and performance. The role of culture and diversity.

Psychological measurement and levels of measurement or scales: nominal, ordinal, interval, and ratio scales.

Classical Test Theory: true score theory, sources of error in psychological testing and the concept of reliability.

Essential statistics: descriptive statistics, measures of central tendency, measures of variability, the normal curve model and non-normal distributions.

Inferential statistics and the logic of significance testing. Parametric tests and assumptions: General Linear Model and analysis of variance, correlation, multiple regression, mediation and moderation, factor analysis. Multicultural approach: introduction to measurement equivalence.

Non-parametric tests: chi-square, linear correlation and regression.

The validation process: test development and item analysis, validity and source of validity evidence. Statistical methods for validation studies: validity and reliability analyses. Essentials of norms and test score interpretation.

Readings/Bibliography

Bernstein, I.H. & Rowe, N. A. (2001) Statistical Data Analysis Using Your Personal Computer. Sage.

Cohen, J. & Cohen, P., West, S. G. & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences, 3rd ed. Hillsdale, NJ, LEA.

Coolican, H. (2014). Research methods and statistics in psychology. Psychology Press.

Hair, JF; Anderson, RE; Tatham, RL; Black, WC (2005). Multivariate data analysis. Prentice Hall International.

Howitt, D. & Cramer, D. (2005). Introduction to Statistics in Psychology. Pearson Education.

Pallant J (2001). SPSS survival manual. Philadelphia, Open University Press.

Tabachnick, B. G., and Fidell, L. S. (2007). Using Multivariate Statistics, 5th ed. Boston, Allyn and Bacon.

Todman, J., & Dugard, P. (2007). Approaching multivariate analysis. An introduction for Psychology. New York: Psychology Press.

Teaching methods

Teacher’s presentations and explanations about the involved methods. Interpretation of statistical outputs; reading, analysis and discussion of research papers and case studies.

Guided exercises about research questions, research designs, hypothesis elaboration, and hypothesis testing.

Homework for practicing the methods and techniques taught using data provided by the teacher. Presentation of homework by students and feedback.

Assessment methods

A) Group written assignment (50% of total grade): Small group (2-3 students): Hypothesis testing, analysis of a data set and report of the results.

B) Individual oral exam (50% of total grade): Discussion about the written assignment and evaluation of general acquired knowledge on psychometrics and testing.

Teaching tools

Power point presentations, journal papers, SPSS databases.

Office hours

See the website of Paola Gremigni