Ch 2 – Psychology’s Scientific Method

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variable
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anything that can change in research (p.26)
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theory
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– a broad idea or set of closely related ideas that attempts to explain observations and to make predictions about future observations – ambiguity: do NOT confuse with hypothesis, which is a smaller and testable component of a theory (proving a hypothesis helps prove a theory) (p.26)
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hypothesis
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– an educated guess that derives logically from a theory; a prediction that can be tested – ambiguity: do NOT confuse with theory, which is too broad to test (p.27) – TESTABLE – in order to test a theory, you must state a hypothesis – a properly designed hypothesis will test a theory by predicting the changes in the dependent variable that are caused by changes in the independent variable
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operational definition
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– a definition that provides an objective description of how a variable is going to mbe measured and observed in a particular study – a specific description of what will be studied (p.27) – makes in possible for an experiment to be repeated by another researcher – an operational definition must be created/stated in order to test a hypothesis
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meta-analysis
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– a method that allows researchers to combine the results of several different studies on a similar topic in order to establish the strength of an effect (p.29)
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descriptive research
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– research that determines the basic dimension of a phenomenon, defining what it is, how often it occurs, and so on (p.29) – incudes: surveys, case studies and interviews
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case study or case history
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– an in-depth look at a single individual (p.31) – example: conducting a series of interviews over a year with an anxiety-disordered student – cannot prove a causal relationship – cannot be repeated
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correlational research
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– research that examines the relationships between variables, whose purpose is to examine whether and how two variables change together (NOT causal) – application: can show links, RELATIONSHIPS between variables, etc. – application: can state ice cream sales linked to increased violence (p.33) – not limited to real-world settings
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third variable problem or confounds
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– the circumstance where a variable that has not been measured accounts for the relationship between two other variables. Third variables are also known as confounds. (p.34)
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longitudinal design
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– a special kind of systematic observation, used by correlational researchers, that involves obtaining measures of the variables of interest in multiple waves over time (p.36) – example: nun study in textbook (followed up with nuns repeatedly over the course of 20 years)
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experiment
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– a carefully regulated procedure in which the researcher manipulates one or more variables that are believed to influence some other variable (p.37)
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random assignment
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– researchers’ assignment of participants to groups by chance, to reduce the likelihood that an experiment’s results will be due to preexisting differences between groups – ensures groups had equal and balanced composition (not biased) – exteremly important aspect of experimental design (p.38)
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independent variable
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– a manipulated experimental factor; the variable that the experimenter changes to see what its effects are (p.38) – it is not getting measured in the experiment – Skinner’s Reserach: food pellet
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confederate
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– a person who is given a role to play in a study so that the social context can be manipulated (p.39)
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dependent variable
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– the outcome; the factor that can change in an experiment in response to changes in the independent variable – essentially what you are measuring (b/c it DEPENDS on other variables) (p.39) – Skinner’s Research: the amount of pecking
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experimental group
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– the participants in an experiment who receive the drug or other treatment under the study–that is, those who are exposed to the change the independent variable represents (p.40) – group taht is subjected to manipulation of the independent variable
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control group
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the particpants in an experiment who are as much like the experimental group as possible and who are treated in every way like the experimetnal group except for a manipulated factor, the independent variable (p.40) – group that is not subjected to manipulation of the independent variable
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external validity
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– the degree to which an experimental design actually relfects the real-world issues it is supposed to address – application: the experiment is only valid in a lab setting (p.42) – Skinner’s Research: the majority of reserach was conducted in a lab with animals–criticized external vaility
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internal validity
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– the degree to which changes in the dependent variable are due to the manipulation of the independent variable – application: there is something wrong with the design of the scientific experiment (something should have been considered that wasn’t, etc.) (p.42)
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experimenter bias
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– occurs when the experimenter’s expectations influence the outcome of the research (p.42) – the tendency to provide subtle clues as to the true nature of an experiment – an exerimenter treating one group of participants differently than another (based on gender, race, appearance, etc.)
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demand characteristics
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– any aspects of a study that communicate to the participants how the experimenter wants them to behave (p.42) – example: smiling/frowning based on how people answer
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research participant bias
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– occurs when the behavior of research participants during the experiment is influenced by how they think they are supposed to behave or their expectations about what is happening to them (p.43)
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placebo effect
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– occurs when particpants’ expectation, rather than the experimental treatment, produce an outcome (p.43) – people feel better simply because they believe they are receiving medication – can cause medication to \”kick in\” faster than it chemically becomes active
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placebo
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– in a drug study, a harmless substance that has no physiological effect, given to particpatns in a control group so that they are treated indentically to the experimental group except for the active agent (p.43)
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double-blind experiment
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– an experimental design in which neither the experimenter nor the participants are aware of which participants are in the experimental group and which are in the control group until the results are calculated (p.43)
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population
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– the entire group about which the investigator wants to draw conclusions (p.45)
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sample
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– the subset of the population chosen by the investigator for study (p.45) – a group of participants observed in a research study (research subjects)
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random sample
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– a sample that gives every member of the population an equal chance of being selected (p.45)
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naturalistic observation
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– the observation of behavior in a real-world setting without distrubing the environment – examples: observing students in classes, observing teachers in classes, observing kids at the mall, etc. (p.46) – researchers cannot intervene in naturalistic observation (would influence the results) – limited to real-world settings
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descriptive statistics
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– mathematical procedures that are used to describe and summarize sets of data in a meaningful way which includes measures of central tendency and measures of dispersion – includes: mean, median, mode, range and standard deviation (p.47) – measures of central tendency: mean, median and mode – measures of dispersion: range and standard deviation
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mean
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– a measure of central tendency that is the average for a sample (p.47) – adding up participants scores and dividing by the number of participants
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median
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– a measure of central tendency that is the middle score in a sample (p.49)
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mode
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– a measure of central tendency that is the most common score in a sample (p.49)
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range
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– a measure of dispersion that is the difference between the highest and lowest scores (p.49)
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standard deviation
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– a measure of dispersion that tells us how much scores in a sample differ from the mean of the sample – more sophisticated version of descriptive statistics – takes squared deviation from the mean – application: frequently results in a normal bell curve (p.49)
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inferential statistics
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– mathematical methods that are used to indicate whether results for a sample are likely to generalize to a population (p.50) – learn whether the data collected supports the hypothesis – over-generalization = a problem, especially with a small sample size –> the subjects may share a characteristic that does not occur across the chosen population
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sampling
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– the act or process of selecting a sample for testing, analyzing, etc. (p.41-42)
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James Pennebaker
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– writing about one’s traumatic experiences is positively related to finding eployement afte being laid of work – research demonstrated that the findings of a correlational study can be the impetus for experiemntal research that determines causation
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cross-sectional design
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A type of correlational study in which variables are measured at a single point in time.

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