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Study Guide for Unit One

by: Brittany Ariana Borzillo

Study Guide for Unit One PSYC3980

Marketplace > University of Georgia > Psychology > PSYC3980 > Study Guide for Unit One
Brittany Ariana Borzillo
GPA 3.7

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Study Materials (including specific things that were stated would be on the test); More detailed notes will be posted by Wednesday.
Research Methods in Psychology
Study Guide
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This 6 page Study Guide was uploaded by Brittany Ariana Borzillo on Monday September 5, 2016. The Study Guide belongs to PSYC3980 at University of Georgia taught by in Fall 2016. Since its upload, it has received 34 views. For similar materials see Research Methods in Psychology in Psychology at University of Georgia.


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Date Created: 09/05/16
Research Development in Psychology: Study Guide Empiricism Empiricism: empirical reasoning, decision making, base conclusions on multiple systematic observations (more observations refines all subsequent observations and conclusions) Theory-Data Cycle: theories generate hypotheses which are tested by data that either supports or challenges the original theory  good theories should be supported by data and also falsifiable o support leads to retesting with other studies, definitions, and methods o lack of support may lead to the adjustment of a theory because the conclusions showed results for an untested variable o complete refutation leads to the development of a new theory  theories cannot be proven Basic-Applied Research Cycle: basic and applied research methods overlap and influence each other (translational research)  Applied o Specific problem needs to be resolved o Solution will fix the problem in real-world context  Basic o Enhance the general body of knowledge Peer Review Cycle: research is run by editors and teams of reviewers, research may be a specific or a general topic, often occurs with publications Journal to Journalism: scientific journals are mainly available to scientists and students but not available to public; journalism is available to the general public but is often misinterpreted Evaluating Resources  Decisions Based on Experience o a single data point cannot be representative of an entire concept o lack of comparison group  control group shows sides with and without the manipulated factor Confounds: alternative explanations for any outcome Empirical Research: theory  research questions  research design/experiment  hypotheses  data  Benefits o One study provides valuable results Probabilistic: inferences are not expected to explain all cases all of the time Bias: intuition leads us to think the easy way and the way that leads us to the results we want  Availability Heuristic: easily remembered events judged more probable than less easily remembered events  Bias by Motivation o Cherry-Picking Evidence o Asking biased questions  Confirmatory hypothesis testing o Overconfidence  Confidence is different than accuracy  “bias blind spot”  the cognitive bias of recognizing the impact of biases on the judgement of 2 others, while failing to see the impact of biases on one’s own judgement Validating Claims Variables: anything that changes Constant: anything that doesn’t change Conceptual Definition: constructs, large ideas that can be broken down in multiple components without an agreed upon definition Operational Definition: how a construct is defined in the context of an experiment Subjective Operationalization: survey/direct questioning supports hypothesis Observed Operationalization: an observed behavior supports the hypothesis Physiological Operationalization: a physiological change supports hypothesis Frequency Claim: used in observational research, one level of one variable for one population is tested, usually expressed as a percentage, need systematic analysis of the particular group, always measured and never manipulated Association claim: used in correlational research, claim that one variable is related to another, always involves at least two (but can be more) variables, variables are always measured and never manipulated Casual Claim: used in experimental research, claim that one variable affects or changes another, requires at least two variables, one variable must be manipulated and the other must be measured, the variables must be related in some way (covariance), whichever variable causes the other must 3 come first (temporal presence), no confounds can manipulate the experiment Independent Variable: manipulated Dependent Variable: measured Validity: conclusion must be appropriate Reliability: whether an experiment has similar results every time its measured Construct Validity: the degree to which a test measures what it claims, or purports, to be measuring, used with all claims External Validity: he validity of generalized (causal) inferences in scientific research, usually based on experiments as experimental validity, used with all claims Statistical Validity: the extent to which a concept, conclusion or measurement is well-founded and corresponds accurately to the real world, used mainly with association and casual claims because frequency claims can only assess error in estimates Type 1 Error: claim a relationship exists when it doesn’t Type 2 Error: claim a relationship doesn’t exist when it does Internal Validity: how well an experiment is done, especially whether it avoids confounding, used only with casual claims Ethics Nuremberg Code (1947): principles – voluntary and have informed consent, address important questions, no unnecessary physical or psychological harm, right to discontinue *should probably know the history behind this one* Tuskegee Syphilis Study (1920s-1970s): ethical issues of harm, respect, and utilizing a disadvantaged group; refused 4 medical care to African Americans with syphilis “for science”; led to basis of APA guidelines Belmont Report: committee in US (1976) developed three main principles for guiding ethical decision making for conducting research on humans {respect for persons, beneficence, justice} Respect for Persons: individuals should be treated as autonomous agents, informed consent, confidentiality, some groups (e.g. minorities) require special protections/rights Beneficence: risk-benefit analysis, fidelity, responsibility, integrity Justice: treat all people fairly, fair balance between people who participate and people who benefit from the results of the experiment APA Ethical Standards*: institutional review board, informed consent, deception, debriefing, animal research, research misconduct *each of these need to be understood specifically for the exam Measurement Categorical (Nominal) Scale: naming or categorizing data Ordinal Scale: a quantitative measurement, indicates direction in addition to providing nominal information Interval Scale: a quantitative measurement, numeric scales in which we know not only the order but also the exact differences between the values, has no true zero which means when an item equals zero there’s something there (e.g. temperature, 0 C) Ratio Scale: a quantitative measurement, a measurement scale that has a numerical difference and ratios between two 5 items; has a true zero which means when an item equals 0 there is none of that variable Reliability: how consistent the results of a measurement are Validity: whether operationalizations are measuring what they’re supposed to Test-Retest Reliability: want r=0.5, measure of reliability obtained by administering the same test twice over a period of time to a group of individuals Interrater Reliability: want r=0.7-0.9, refers to statistical measurements that determine how similar the data collected by different raters are Internal Reliability: want r=0.7, need at least two items, questions verified with Cronbach’s alpha, more data collected is more ideal, assesses the consistency of results across items within a test Empirical Validity: describes how closely scores on a test correspond (correlate) with behavior as measured in other contexts Criterion (Predictive) Validity: the extent to which a measure is related to an outcome; often divided into concurrent and predictive validity – concurrent validity refers to a comparison between the measure in question and an outcome assessed at the same time, predictive validity compares the measure in question with an outcome assessed at a later time Convergent Validity: refers to the degree to which two measures of constructs that theoretically should be related, are in fact related Discriminant Validity: tests whether concepts or measurements that are not supposed to be related are, in fact, unrelated 6


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