quiz 1 + 2 review

theory

 a principle (idea) or a set of principles that seek to explain how something works - can be used to explain empirical data

hypothesis/predictions

testing the relationship between two variables - uses theory and previous empirical research

variables

something that varies/subject to change

independent variable

variable that is manipulated

dependent variable

variable that is measured

operational definitions/operationalization

defines hypothetical construct - abstract concept to a measurement or a particular way of manipulating or measuring the variable

internal validity

the ability to draw proper cause-and-effect relationships between variables with no cofounding variables or biases

external validity

a generalization of the research onto other populations 

construct validity

measurements intending to measure what its to measure - ensures that the operational definition matches the theoretical concept

hypothetical construct

unobservable, non-measurable, and theoretical concept used in psychology and science to explain or mediate observed behaviors or phenomena

reliability of measurement

measuring with as little error as possible - are the measurements reliable over multiple trials?

fundamental difference between experimental and non-experimental research 

experimental research

1. Seeks to establish cause/effect relationships causality 

2. Presence of independent and dependent variable 

3. Experimental manipulation of a variable (independent variable) 

4. Random assignment to conditions 

non experimental research

1. observes natural circumstances with no intervention

observational research

a passive, non-interference, and behavior recording type of research

pros of observational research

raw data as you don’t manipulate anything

cons of observational research

no knowledge about what has happened, limits conclusions one can make

pearson’s R/correlation coefficient

a measurement of the strength and relationship between two variables

• +1: Perfect positive linear relationship

• 0: No linear relationship

• -1: Perfect negative linear relationship

positive correlation

more of A = more of B (ex.more studying = better grades)

negative correlation

more of A = less of B (ex. more sunscreen = less sunburn)

quasi-experiments

non-experimental designs that compare two groups without random assignment to conditions 

strengths of quasi experiments

• high external validity

• lower cost to run

weaknesses of quasi experiments

• lower internal validity

• risk of cofounding variables

simple experiments

establishing cause-and-effect relationships by the manipulation of one variable (experimental) and a control variable 

• includes random assignment and manipulation of variables 

• allow for causal explanations -> leads to high internal validity

multiple-group designs

an experiment where there is more than one IV 

• for more comparisons; tells more about the relationships between variables and conditions 

between-subject experiments

participants are tested in only one condition (group A or group B)

within-subjects experiments

participants are tested in multiple independent variables (group A and group B)