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70 Cards in this Set
- Front
- Back
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The need for behavioral science |
The “folk” understanding of behavior is severely limited because it is: - usually postdictive, not predictive (based on non-specific clichés) -often wrong (even our recent perceptions) - doesn’t recognize the importance of factors outside our awareness |
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Item-to-total correlations |
a correlation to see how well one item on a survey agrees with other items. ex) does item 20 correlate with the sum of items 1-19? (pearson correlation) |
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Surveys |
a series of self report measures administered either through an interview or a written questionnaire. These are the most widely used to collect descriptive data about a population |
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questionnaires |
a set of fixed format, self-report items that is completed by respondents at their own pace, usually without supervision |
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Pros and Cons of questionnaires |
Pros: cheaper, produce more honest answers, less likely to be influenced by the experimenter Cons: response rates from the general population are sometimes low, which effects the results because it could be a certain type of person who is responding, the experimenter has no way of knowing what order the participants answered the questions in, which could also alter results |
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interview |
questions are read to the respondent , either in person or over the phone |
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Values VS Empirical facts |
Values: personal statements based on opinions Facts: objective statements based on empirical study |
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Hindsight bias |
the bias that people have to believe they could have predicted something that they could not have |
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The Scientific Method |
The Scientific Method: the set of assumptions, rules, and procedures that scientists use to acquire new knowledge and integrate previous knowledge.
1. Observe and describe a phenomenon. 2. Formulate a hypothesis to explain it. (A hypothesis is a reasoned guess or an educated proposition.) Folk explanations stop at this step. 3. Use the hypothesis to generate predictions about the existence of other phenomena or observations. Sometimes there are two hypotheses that generate competing predictions. 4. Gather the data to test the predictions. Often, but not always, this involves performing an experiment. 5. Evaluate whether predictions are supported. Revise hypothesis accordingly. Repeat steps 3 and 4. |
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Falsifiability |
In order for something to be scientifically testable, it must be able to have a negative result. You can't prove something is true if you can't prove it is false. |
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Applied VS general Research |
general: answers fundamental questions about behavior, simply to understand how things work Applied: investigates issues that have implications for everyday life and provide solutions to everyday problems |
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Descriptive Research Design |
This type of research provides a "snapshot" of thoughts, feelings, or behaviors at a given time it can be either qualitative or quantitative in design |
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Experimental Research Design |
the active creation or manipulation of a given situation or experience for two or more groups or individuals it is designed to create equivalence between the individuals before the experiment begins |
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Correlation Research Design |
involves the measurement of two or more variables, and analysis of the relationship between them statistical measures such as pearson correlation are used to determine how strong the relationship is |
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Pearson Correlation |
represented as the letter r ranges from -1 to 1 if it is negative, there is a correlation of the two things going together in opposite directions (as one increases, the other decreases), while if it is positive then they covary the closer to -1 or 1, the higher the correlation. The closer to 0, the less strong the correlation is |
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Weaknesses of Correlation |
cannot be used to identify causal relationships. When you think one is causing the other, the reverse may be true. additionally, there could be a third variable that is influencing them both to change. it doesn't answer the question of why |
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elements of experimental research |
Experiments have 3 inter-related elements.
1) Comparison – compare results under different conditions to rule out certain explanations and support others. 2) Control – attempt to compare conditions that are equivalent in all respects, except for the experimental manipulation. 3) Manipulation – alter one (or more) variable(s) or conditions. This manipulated variable is called the independent variable. The variable that might change in response is the dependent variable. |
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Random Assignment |
Participants are randomly assigned to either the experimental of control group in order to make the two groups as similar as possible |
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Independent Vs. Dependent variable |
The variable that is being manipulated is the independent variable. |
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observer/researcher expectancy effect |
the person conducting the study is somehow influencing the study, thus effecting the outcome of the study. The best way to avoid this is to have the researchers be blind to which group the participants are assigned |
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Subject expectancy effect |
when a subject knows (or suspects they know) what group they belong to, they may alter their behavior in a way that effects the data by trying to do or be what is predicted (or trying not to). |
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Placebo |
a placebo is a pseudo treatment administered to participants so that they think they are being given the experimental treatment, thus controlling for their expectancy effect. (everyone will think they are going to see a change, so the difference between the two is still valid) |
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Double Blind |
both the researcher and the participant are unaware of which group the person is assigned to in an effort to remove both observer and subject expectancy effect |
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Ways to Generate Research |
1. Identify a practical problem
2. Identify an empirical pattern 3. Finding limiting conditions; developing alternative explanations 4. Applying a hypothesis to new domain |
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What is the purpose of reading scientific literature? |
The IRB and government granting agencies require research on previous text. It will allow you to answer the following questions: Has your topic already been investigated? Has your specific study already been done? What are the most important issues to investigate? What are the most important variables to measure? What’s the most effective and ethical method for investigating this issue? |
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primary vs. secondary sources
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Primary sources come from the primary research body- this will have a methods and results section ***Meta-analysis is a primary source secondary sources are reviews of research that have been completed, which do not have a methods or results section, and often cite many sources |
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Laws |
principles that are well-established and extremely general. There are very few general laws in psychology. But for an evolutionary psychologist, the theory of evolution by natural selection is clearly a law; for a neuroscientist, the “neuron doctrine” is a law. Very little research is designed to test laws, since hardly anyone doubts they are true. (e.g. evolution by natural selection produces psychological and behavioral adaptations)
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Theories |
broad principles, but not as broad as laws; must be compatible with laws yet be logically independent of them; there is less certainty about their validity. (e.g. sports function as a display in social selection / sexual selection)
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Research Hypotheses VS Theories |
Theories are not generally directly tested because they are quite broad; instead, principles or logical deductions which follow from them are tested. These are research hypotheses; any good theory will provide many research hypotheses. If the hypotheses that follow from a theory are regularly tested and no support for them is found, the theory must eventually be rejected or at least modified. (e.g. better athletes will generally be more attractive)
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predictions |
the “nuts of bolts” of what variables are measured in observational and experimental studies; and how the variables are expected to relate to one another. If the falsifiable prediction is repeatedly not supported, the research hypothesis must be rejected or modified.
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inductive vs deductive methods |
Deductive deduces something from a hypothesis. The theory tells you what to look for. "top down" Inductive is from observations in data or the real world that result in developing a way to test these things. "bottom up" |
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Informed Consent |
Informed Consent is process, not just a signature. Process includes:
1. Verify eligibility to give consent (age, mental state). 2. Explain procedures and events, who is conducting research, and how data will be used and protected. 3. Explain potential costs and benefits. 4. Inform of rights (e.g. leaving). Participants rarely drop out once they start. - Possibly because informed consent addresses concerns - But possibly because of social pressure |
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Power Differentials |
Researchers inherently have power over participants; they shouldn’t abuse it.
-promising rewards and not delivering them - wasting the participant’s time -antagonizing someone for any reason that has no research purpose -not protecting privacy or otherwise not living up to informed consent claims |
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Privacy |
Data should remain confidential
- in presentations and publications - as much as possible, in researcher’s own records - 3rd parties shouldn’t be able to link data to names Breaking the link between data and name is good practice. Data should be secured. Sometimes participation can be anonymous. |
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Deception |
Deception is defined as a participant not being fully informed about the true nature of research before deciding to participate.
- can involve actively giving misinformation - can be passive, e.g. exposing someone to a scene and then giving a “pop quiz” about it The main justification for deception is that many important psychological issues could not be studied without it. |
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Economists view of deception |
Economists argue that trust is a public good. By deceiving, psychologists use up the trust and pollute the participant pool. Eventually all participants come into studies expecting to be deceived.
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APA requirements for deception |
APA and research boards recognize the need for deception but:
the minimum amount of deception necessary should occur participants should be told of deception afterwards deception should be used only when it cannot be avoided the deception should not result in harm |
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Debriefing |
Debriefing occurs at the end of a study.
Its purposes are to restate (or more fully explain) the nature of the study, ensure the well-being of participants, and allow questions about the research. If deception was used, the deception should be revealed. Prior to this, the researchers may also ask the participants if they were suspicious about anything in the study. Sometimes debriefing may involve activities to undo any changes that might have occurred during the study. |
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What is an IRB? |
"institutional review board" required by the government of any institution that receives federal funding, even if it isn't being used on the research The IRB’s primary goal is to make sure that the costs (including risks) and benefits of the research, especially to participants, are fully identified. The risks involved must be justified by the potential knowledge gained. The IRB does not guarantee the soundness of the research, that the researchers will follow the protocol they submitted, or that researchers will not be fraudulent. |
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Composition of IRBs |
IRBs will have at least 5 members, and at least one of these will be a non-scientist, and at least one will not be affiliated with the institution where the research will be conducted.Scientists can’t serve as members of the IRB when their own project is being evaluated.
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conceptual vs. measured variables |
conceptual: the ideas that form the basis of a hypothesis. (e.g. self esteem, depression, cognitive development) Measured: numbers that represent the conceptual variable |
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Operational Definitions |
a precise statement of how a conceptual variable is turned into a measured variable |
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Converging Operations |
Using more than one technique/research design to study the same thing with the hopes that they will produce similar findings |
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Nominal Variables |
used to name or identify particular characteristics (e.g. religions, genders, races) we will sometimes assign numbers to nominal variables, but the numbers are arbitrary (race in our lab) |
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Quantitative Variables |
uses numbers to indicate the extent to which a person possesses a characteristic of interest. (e.g. height, BMI, time to complete a puzzle) |
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What are the three types of Quantitative scales? |
Ordinal, ratio, and interval scales |
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Interval Scales |
equal distances between scores correspond to equal changes in the conceptual variable. ALMOST NEVER USED IN PSYCH (e.g. The temperature difference between 10°F and 20°F is the same temperature difference as between 40°F and 50°F. )
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Ratio Scales |
Ratio scales: like interval scale but also have a true zero point so that scales values can be multiplied and divided meaningfully.***statistical options are greatest on this type of scale
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Ordinal Scales |
the order indicates whether there is more or less of something but they don’t indicate the exact interval between them.
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self report VS behavioral measures |
self report is asking people to report what behaviors they exhibit, while behavioral actually measures the true behavior |
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Free format (types and examples) |
Projective Measures include the Rorschach inkblot test and the Thematic Apperception Test (TAT).
Associative Lists Measures Think-aloud Measures involve participants describing their thoughts as they complete a task. A major drawback of all free format measures is that coding data is time consuming. |
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Fixed format types and examples |
some address unambiguous concepts (like circling ones race/ethnicity) while others use a scale. Number scales of agree to disagree can be used, pictures can be used, rating of importance, etc. |
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Likert Scale |
a series of items that indicate agreement or disagree with the issue that is to be measured, each with a set of responses on which the respondents indicate their opinions. (e.g. the rosenburg self-esteem) |
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Guttman scale |
a fixed format self report scale in which the items are arranged in a cumulative order such that it is assumed that if a respondent endorses or answers correctly any one item, he or she will also endorse or correctly answer all of the previous scale items. |
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reactivity |
changes in responding that occur when individuals know they are being measured |
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self-promotion |
a type of reactivity that occurs when research participants respond in ways that they think will make them look good. |
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random error |
chance fluctuations in measurement that can be controlled by evenly distributing the error throughout the two samples |
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systematic error |
influence of conceptual variables that are not being studied having an effect on the results of the study. These do not "self cancel" and therefore systematically increase or decrease the results of the study. |
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test-retest reliability |
the extent to which score on the same measured variable correlate with the each other on two different measurements given at two different times |
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Equivalent forums |
two different measures that are equivalent are given at two different times. the goal is that they are enough alike that they will measure the same thing accurately. (e.g. ACT) |
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internal consistency |
the extent to which scores relate to each other and thus are all measuring the true score rather than random error |
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acquiesent responding
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"a yes man", when participants are responding yes to everything. a way to combat this is reversed items |
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Cronbach's alpha |
an estimate of the average correlation among all of the items on the scale and is numerically equivalent to the average of all possible split-half reliabilities |
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Construct Validity |
the extent to which a measured variable actually measures the conceptual variable that it is designed to measure |
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Face validity |
the extent to which the measured variable appears to measure the conceptual variable |
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Content Validity |
the extent to which the measured variable appears to have adequately covered the full domain of the conceptual variable |
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Convergent Validity |
The extent to which a measured variable is found to be related to other measured variables designed to measure the same conceptual variables
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discriminant validity |
the amount to which a measured variable is found to be unrelated to other measured variables designed to measure different conceptual variables |
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Predictive Validity |
The amount to which a a self report measure correlates (predicts) a future outcome |
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Population |
the entire group of people that the researcher would like to know about |
