2.2 Psychologists Use Descriptive, Correlational, and Experimental Research Designs to Understand Behavior Flashcards
research design
the specific method a researcher uses to collect, analyze, and interpret data
Descriptive research
research designed to provide a snapshot of the current state of affairs
Correlational research
research designed to discover relationships among variables and to allow the prediction of future events from present knowledge
Experimental research
research in which initial equivalence among research participants in more than one group is created, followed by a manipulation of a given experience for these groups and a measurement of the influence of the manipulation
case studies
descriptive records of one or more individual’s experiences and behavior
survey
- a measure administered through either an interview or a written questionnaire to get a picture of the beliefs or behaviors of a sample of people of interest.
- The people chosen to participate in the research (known as the sample) are selected to be representative of all the people that the researcher wishes to know about (the population).
naturalistic observation
research based on the observation of everyday events
descriptive statistics
numbers that summarize the distribution of scores on a measured variable
normal distribution
A data distribution that is shaped like a bell
central tendency
the point in the distribution around which the data are centered
dispersion
spread
arithmetic mean
the most commonly used measure of central tendency
median
- used as an alternative measure of central tendency when distributions are not symmetrical.
- the score in the center of the distribution, meaning that 50% of the scores are greater than the median and 50% of the scores are less than the median
mode
represents the value that occurs most frequently in the distribution
range
of the variable is the maximum observed score minus the minimum observed score
standard deviation
symbolized as s, is the most commonly used measure of dispersion
scatter plot
a visual image of the relationship between two variables
Pearson correlation coefficient
- The most common statistical measure of the strength of linear relationships among variables
- value: ranges from r= –1.00 to r = +1.00
Multiple regression
a statistical technique, based on correlation coefficients among variables, that allows predicting a single outcome variable from more than one predictor variable
common-causal variable
a variable that is not part of the research hypothesis but that causes both the predictor and the outcome variable and thus produces the observed correlation between them
spurious relationship
a relationship between two variables in which a common-causal variable produces and “explains away” the relationship
independent variable
an experiment is the causing variable that is created (manipulated) by the experimenter
dependent variable
an experiment is a measured variable that is expected to be influenced by the experimental manipulation