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Intro to Research Midterm Study Guide

by: Kim Notetaker

Intro to Research Midterm Study Guide

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This is a detailed study guide for our midterm. This midterm and study guide is for Chapters 1-7.
Intro to Research Methods
Study Guide
PSYC, research, Studyguide
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Date Created: 10/05/16
PSYC 2200 Study Guide – Midterm Exam I. The Scientific Approach, Hypotheses, and Theories (Ch. 1 and 2)  Why study behavioral research methods? o To be good producers and consumers of research.  The job of a research producer  Act as an empiricist by systematically observing the world.  Test theories through research and adapt those theories based on  resulting data.  Use research to examine both basic and applied research.  Test why, when and for whom.  Make your work public by submitting to academic journals.  Talk to the media about your work.  o Empiricism: using evidence from the senses or instruments that aid the  senses as the basis for conclusions  o Theory­hypothesis­data cycle  Theory: set of statements that describes general principles about  how variables relate to another.  Hypothesis: a way if stating the specific outcome, the researcher  expects to observe if the theory is correct.  Data: a set of observations to test your hypothesis.  HARKing: Hypothesizing After Data Is Known. When you write  about research, should you tell a good story or every detail of the  research?  Characteristics of a good theory  Supported by data: You are often slow to give up a theory  (Kuhn’s paradigm shift).  Falsifiability: the possibility of collecting data and proving a  theory wrong.  Parsimony: “all things being equal,” which means that simple is best. o Types of research questions  Basic research: the goal to enhance the general body of knowledge. PSYC 2200  Applied research: conducted with a particular problem in mind  with the hope of improving things. The data is applied to the  problem.  Translational research: when you use lessons from basic research  to develop and test applications. o Questions about why, when, and for whom  Mediating variables: explaining why A is related to B (cause).  Moderating variables: identify when and for whom a is related to  B. o Talking to the media  Pros    A bigger audience.  Help people.  People learn what you actually do.  Cons  Often misquoted.  Often misinterpreted.   Often misses the point.   Other ways of learning about human phenomena o Experience  Comparison groups: this allows us to compare what would happen  to both groups with and without the thing you are interested in.  Confounds: these are alternative explanations for the same effect.  Probabilistic nature of research: you can’t take into account  enough cases to be sure of the cause and the effect. o Intuition  Availability heuristic: things that easily come to mind seem more  likely.  Confirmatory hypothesis testing: asking questions in a way that  you get the answer that you want.  Bias blind spot: belief that one will not be biased but they are. o Authorities: can’t always trust them. II. Defining Variables & Introduction to the Four Validities (Ch. 3) PSYC 2200  Variables: anything you can measure or manipulate. o Levels: the value of the variable in the study. o Constants: something in the study that you can change but will not  change and it has only 1 level. o Measured variables: a variable that is observed or recorded as it occurs  naturally. o  Manipulated variables: the variable that the researcher controls and  changes. o Dependent variable: the outcome variable; always measured and never  manipulated. o  Independent variable: the predictor variable; always manipulated but  can be measured. o Defining variables  Conceptual definition: the precise definition or description of the  construct.  Operational definition: the specific way a variable will be  manipulated or measured.  Validity of a study’s conclusions o Definition of validity: the appropriateness of the conclusion or the  decision. o Construct validity: how well did the researcher operationalize (use) each variable? o External validity: how well do the results generalize or represent the  people outside the study? o Internal validity: in the experiment; how sure are you that the change in  the dependent variable is from the independent variable?  Confounds: a possible alternative explanation for a research  finding. o Statistical validity: how well does the number data support the  researcher’s conclusion?  Margin of error: indicates the probable true value in the  population.  Statistical significance: the probability that some of the results  occurred by chance or that the result from the sample is so extreme that it couldn’t have come from the population.  PSYC 2200  Type I errors: false alarm or a false positive; saying a relationship  exist when one doesn’t. This error is more tolerated than a type 2  error.   Type II errors: false negative; saying that no relationship exists  when one does. III. Introduction to Measurement (Ch. 5)  Scales of measurement o Nominal: values are just labels and categories.  An example would be, are you happy? Yes or no o Ordinal: the rank ordering and the amount of space between the ratings  doesn’t matter. o Interval: the equal differences between the numbers reflects the equal  differences on the dimension being measured. This has NO true zero or  absolute zero.  An example would be how happy you are on a scale of 1­7. 1  being the least happy and 7 being the most o Ratio: the interval scales plus a ‘true zero.’ This is a good measure of  behavior.  An example would be asking how many times did you feel happy today?  Reliability of measures o Reliability: the consistency, stability or dependability of a measure. o Correlation coefficients: measures the strength and direction of the  association between 2 variables  Strength: how well can you predict one thing by knowing about the other? (ranges from 0 to +/­ 1)  0 = no correlation  .1 ­ .3 = small correlation  .3 ­ .5 = medium correlation  .5 or larger = large correlation  Direction: as one variable goes up does the other variable go up or  down? o Test­retest reliability: the consistency of the results over time. o Inter­rater reliability: consistency over observers. PSYC 2200 o Internal reliability: consistency over observers.  Cronbach’s alpha:   Step 1: Compute all possible connections between the  items. (item 1 with item 2 and so forth.)  Step 2: Take the average of these correlations.  Step 3: Fancy math with the average of the correlation and  the number of items = Cronbach’s alpha  .70 standard  Validity of measures o Validity: the degree to which a measure is an accurate representation of  the construct we want to measure. o Face validity: Does the measure seem like a plausible one, given the  construct of interest. o Content validity: Does the measure capture all parts of the construct of  interest? o Criterion validity: Is the measure related to relevant objective outcomes?  Known­groups paradigm: this is when you take groups you know  to be different and give them the measures. o Convergent validity: Is the measure related to other measures that assess  similar constructs? o Discriminant validity: Is the measure NOT related to other measures that assess different constructs? IV. Surveys and Observations (Ch. 6)  Self­report measures o Open­ended questions: allows people to respond to the questions freely.  Advantage: is that is allows people to tell you what is important to  them whether you thought about it or not.   Disadvantage: is that you might never get the stuff that you care  about; coding the results will be time consuming for you and the  participant. o Closed­ended questions: provide people with specific rating dimensions  of interest.    Forced choice questions: for nominal data.  Likert scale: for interval data.  PSYC 2200  Semantic differential scale: a scale from something like foolish to  wise. o Question wording  Leading questions: makes one answer seem clearly better or more  correct than the others.  Double­barreled questions: asking two question at once.  Negatively worded questions: using negations makes questions  more difficult to understand. o Question order: responses in earlier questions can affect the answers of  later questions. o Response sets  Acquiescence: the tendency to say yes to everything no matter  what you ask.  Solution would be to include reverse scored items.  Fence sitting: when you stay close to the middle of the scale.  Solution to this would be even number of scale points.   Social desirability: concern over the impression of one’s responses  might convey.   Ways to reduce its influence.  Anonymity and confidentiality.  Give people a social desirability scale and account those  score when it comes to your analyses.  Include a few items to catch social desirability responding.  Use surreptitious measures.  Social desirability scale  Observational measures o Naturalistic observation: observing behavior as is naturally occurring  with no intrusion of the researcher.  o Contrived observation: observe the behaviors in a research setting.  Participant observation: becoming part of the world you wish to  observe as a researcher. o Undisguised observation: the participants will know they are being  observed. o Disguised observation: participants don’t know they are being watched. PSYC 2200  Reactivity: people may change their behavior because they know  they are being watched  Partial concealment strategy: participants know they are being  observed but don’t know why. o Options for recording behavior  Narratives: full descriptions of the behaviors.  Checklists: count the occurrences of specific behaviors.  Temporal measures: know the timings of the behaviors.   Duration: how long the behavior lasted.  Latency: time between an event and the response.  Rating scales: outside parties make subjective about behavior on  specific measures. o Observer effects  Observer bias: observers’ expectations can influence their  interpretation of the participant’s behavior  Observer expectancy effects: observes’ expectation can actually  influence the participants’ behavior. V. Sampling (Ch. 7)  Terminology o Population: entire set of people you are interested in. o Sample: the subset of people you actually study. o Census: a study that involves the entire population.  Representative sample: all members of the population have an equal chance of being included in the sample.  Biased (unrepresentative) sample: some people in the population have a much  better chance being included in the sample than others. o Self­selection: sampling from those who volunteer.  Random sampling (probability sampling): the process of creating a  representative sample, such that each population member has an equal chance  of selection. o Simple random sampling: sample chosen completely at random from the population.  Sampling frame: a full list of people in the population.  o Cluster sampling: 3 Steps. PSYC 2200  Step 1: break population into clusters.  Step 2: randomly sample the clusters.  Step 3: use everyone from the selected cluster.  Multistage sampling: similar but Step 3 changes.  Step 3: randomly sample people from each randomly  selected cluster. o Stratified random sampling: similar to cluster sampling, but uses  demographic groups instead clusters.  Step 1: identify the demographic groups for which you want  to ensure appropriate representations.  Step 2: determine the percent representation of each group  within the population.  Step 3: randomly sample the right number of people from  that group to ensure correct percent representation within the sample.  Oversampling: randomly sample MORE THAN the right number  of people o Systematic sampling: pick a number and you sample that number person that goes by. o Challenges with random sampling  over­represents people who are “reachable,” and under­represents  those who aren’t.  even people who are reachable may not want to participate.  Ways to increase response rate   Follow up.  Give incentives.  Check how people who respond differ than those who don’t.  Biased sampling o Convenience sampling: sampling from those who are readily available to participate. o Purposive sampling: non­randomly recruiting a particular type of  participants.  An example question: how many cancer patients see a therapist at  least once peer week. o Snowball sampling: recruitment via participant’s social networks. PSYC 2200 o Quota sampling: pick a target number of participants in a particular  category, recruit until you get that number. VI. Research Ethics and the Publishing Process (Ch. 4)  The Belmont Report: a broad set of principles to guide research with human  subjects. Motivated by the Tuskegee Syphilis Study. o Principle of respect for persons: informed consent, particularly for  groups with reduced autonomy. o Principle of beneficence: protect participants from harm, and ensure  well­being. o Principle of justice: fair balance of benefits and costs associated with  research participants.  APA standards o Institutional review board (IRB): committee that reviews research at  universities and schools to ensure ethical conduct. o Coercion: the explicit or implicit suggestion that someone who chooses  not to participate will suffer negative consequences. o Undue influence: offering an incentive too attractive to refuse. o Informed consent: must provide the participants with information about  the study, particularly risks and benefits so they can decide if they want  to participate.  Information included and excluded  Reasons informed consent can be problematic (3)  People won’t behave naturally.  Some people can’t give consent.  Consent may be impractical or impossible to obtain.  Conditions under which informed consent can be waived (2)  Behavior is fully public.  Minimal risk. o Deception: researchers withhold some details about the study either  though omission or commission.  Confederates: an actor playing a specific role for the study.  Objections to deception (2)  Moral argument. PSYC 2200  Pragmatic concerns. o Debriefing: informing participants about all aspects of the study after the study is over. o Research misconduct  Plagiarism: misrepresenting the ideas or words of others as one’s  own.  Data fabrication: inventing data.  Data falsification: inappropriately messing with data. o Research with animals  Replacement: find alternatives when possible.  Refinement: minimize or eliminate animals’ distress.  Reduction: use as few animals as possible.  Institutional Animal Care and Use Committee (IACUC)  Arguments in favor (3)   Benefits for humans and animals.  All efforts are made to avoid and minimize suffering.  Extent or cruelty is exaggerated.  Against (2)  No creature should suffer.  Violated the principles of justice.   The publication process o Steps in submitting a paper for publication (4 steps)  Manuscript is sent to one journal for consideration.  Editor assigns paper to associate editor.  Associate editor identifies 2­4 reviewers.  Write review and decide publish ability.  Associate editors  Experts in the field.  Reviewers  Experts in the field. o Possible outcomes (4) and which is most and least common  Accept as is. (Least common)  Accept with minor revision.  Revise and resubmit. PSYC 2200  Reject. (Most common) o Criteria for publication (6)  Significance of the question.  Interestingness.  Methods high in construct, internal and external validity.  Appropriate analyses and interpretation of data.  Good writing. 


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