EXPERIMENTAL PSYCHOLOGY Alla Chavarga Tuesdays 9:00-11:20am 2412J or 6:10-8:30pm 432-IA Email: alla.chavarga@gmail.com LABS: MW 6:10-9:45pm 3106J Kravitz  MW 6:10-9:45pm 4109J Ergun  TR 11:30-3:05pm 3106J Fein  TR 11:30-3:05pm 4109J Hazan

Getting Started & Measurement CHAPTER 2 & 3 Getting Started & Measurement Lecture Outline What are the different types of research? Basic Concepts (Data, Variables, Relationships) How do we develop research questions? Scales of Measurement Evaluating Measures

VARIETIES OF PSYCHOLOGICAL RESEARCH Basic Designed to describe and understand fundamental psychological phenomena 01 Applied Designed to shed light on the solution to real-world problems 02

VARIETIES OF PSYCHOLOGICAL RESEARCH Laboratory Greater Control Low mundane realism 01 Field More realistic High mundane realism 02 Mundane realism – how closely a study mirrors real-life experiences Experimental realism – the extent to which a study has an impact on the subjects, forces them to take the matter seriously, and involves them in the procedures

VARIETIES OF PSYCHOLOGICAL RESEARCH Quantitative Includes quantitative data and statistical analysis 01 Qualitative Includes narrative descriptions, content analyses, interviews 02 Much research includes elements of both: Depression and anxiety studies Case studies of drug/alcohol users

BASIC CONCEPTS Variables Sampling and Measurement Statistical relationships between variables Differences between groups Correlations between quantitative variables CORRELATION IS NOT CAUSATION How do we establish causation? Can we ever? Variables Independent Dependent Sampling and Measurement

How do we develop research questions? Our own observations Example: Kitty Genovese Serendipitous events Discovering something while looking for something else (”edge detectors”) Hubel and Wiesel (1959, 1962): “edge detectors”

How do we develop research questions? Research teams and the “What’s next?” question Programs of research Series of interrelated studies Research teams and the apprentice model Replication and Extension Exact replication is rare (however, the norm in Pavlov’s lab; training new workers) Extension: partial replication with new features added to extend the findings

MEASUREMENT What do we measure? How do we measure it? 01 Develop Measures from Constructs Construct: a hypothetical, explanatory variable that is not directly observable. Select variables that represent or are involved in constructs 02 03 Operationalize variables Operational definitions define concepts and labels by the way they are measured.

MEASUREMENT How do we measure: Height? Intelligence? Depression? Attractiveness? Passive aggression?

Understanding of gravity Visuospatial Sketchpad MEASUREMENT Understanding of gravity Visuospatial Sketchpad Using habituation to define the construct “understanding of gravity” as preferential looking / time spent looking (seconds). Construct: Understanding gravity Operational definition: time spent looking at each test event Construct is defined as response time to a mental rotation task (seconds, milliseconds). Construct: visuo-spatial sketchpad Operational definition: time to complete each mental rotation task

Measuring: assigning numbers to events, characteristics, or behaviors SCALES OF MEASUREMENT Measuring: assigning numbers to events, characteristics, or behaviors Category labels or names; no numerical order. 01 NOMINAL Ranks, positions in order; intervals on scale not equal. 02 ORDINAL Numerical scale, equal intervals, no absolute zero. 03 INTERVAL Numerical scale, equal intervals, absolute zero. 04 RATIO

IDENTIFY THE SCALE School year (freshman, sophomore, etc) Gender Amount of change in your pockets Social Security # Nominal Ordinal Interval Ratio

EVALUATING MEASURES Reliability The extent to which a measure produces the same result when applied to the same person under the same conditions; the consistency of a measure Over time (test-retest reliability) Across items (internal consistency) Across researchers (inter-rater reliabilty)

EVALUATING MEASURES Validity The extent to which the scores from a measure represent the variable they are intended to. Face validity Content validity Criterion validity Convergent validity Discriminant validity