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Chapter 3

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York University
PSYC 2130
Krista Phillips

Chapter 3: I. Psychology's Emphasis on Method  Research process is sometimes more important than answers  Goal to improve on hypothesis constantly being developed  Emphasis on methods by which knowledge can be obtained o More concerned with better understand human nature than with specific facts II. Scientific Education and Technical Training  Technical training teaches one to use what is already known  Scientific training teaches one to explore the unknown  Research exploration of the unknown o Essential aspect is the gathering of data III. Quality of Data a. Reliability  Reliable data measurements that reflect what you are trying to assess and are not affected by anything else  Measurement error (error variance) the cumulative effect of such extraneous influences o State, trait  4 things can undermine reliability: o Low precision measurements should be taken as exactly as possible, as carefully as possible  Great care be taken in recording data, scoring them correctly, and entering them carefully into the data base o The state of the participant in the study might vary for reasons that have nothing to do with the study itself o The state of the experimenter o The environment in which the study is done  4 ways to improve reliability: o Be careful double check all measurements, proofread, make sure procedures are understood by assistants o Use a constant, scripted procedure for all participants  Procedure written on the research protocol should be followed, no matter what happens o Measure something that is important, rather than something that is trivial o Aggregation or averaging  When everything is averaged, errors cancel each other out  Spearman-Brown formula in psychometrics random errors tends to cancel each other out b. Validity  Degree to which a measurement actually reflects what one thinks or hope it does  For a measure to be valid, it must be reliable o But a reliable measure not necessarily valid  The concept seems to invoke a notion of ultimate truth o On the one hand, you have ultimate, true reality; on the other hand, you have a measurement o If the measurement matches ultimate, true reality, it is valid  Constructs something that cannot be directly seen or touched, but which affects and helps to explain many different things that are visible  Construct validation the process of testing the theory behind a construct (intelligence or sociability ) c. Generalizability  Is the result you get with one test equivalent/generalizable to the result you get using a different test  Generalizability over participants o To what degree can researchers draw valid conclusions about people in general if all they study are college students?  Failures of generalizability: o Gender biasmost men are not willing to participate in experiments- and the ones that sign up are unusual men o Show vs. no show results of research depend on the attributes of the people who show up for experiment  Not representative of the much larger population o Cohort effects tendency of a group of people living at a particular time to be different in some way from those who live earlier or later o Ethnic and cultural diversity fail to represent ethnic minorites IV. Research Design  A plan that should be followed a. Case Method  Closely studying a particular event or person in order to find out as much as possible  Used all the time  Advantages: o It describes the whole phenomenon and not just isolated variables o Can be a source of ideas o Sometimes the method is absolutely necessary  Disadvantage: not controlled b. An Experimental and a Correlational Study  Experimental o Get a group of participants, randomly divide in 2 groups, say something to one group and nothing to the control group, give test, write results down, get average, to t-test (statistical test)  Correlational o Give all participants a questionnaire first then the test, see if anxiety hurts performance, scatter plot (scores for anxiety on x-axis and performance on y-axis) –see correlation c. Comparing the Experimental and Correlational Methods  Both methods attempt to assess the relationship between 2 variables  The statistics used in the 2 studies are interchangeable o The t statistic from the experiment can be converted, using simple algebra, a correlation coefficient (traditionally denoted by r) and vice versa  Experimental the presumably causal variable (anxiety) is manipulated o You can never be sure exactly what you have manipulated, of where the actual causality was located o Can create levels of a variable that are unlikely or even impossible in real life  Exaggerated variables o Experiments often require deception o Sometimes experiments are simply not possible o Whether one variable can affect another  Correlational same variable is measured as it already exists, without manipulation o Either of the 2 variables might actually have caused the other  Structural equation modeling o How often or how much a variable can affect another  Third-variable problem affects both correlational and experimental designs in different ways d. Representative Design  Are the results of what happens beyond the confines of the laboratory? o Participants are not the only factors which researchers should generalize  There are other stimuli and responses  Representative design Egon Brunswik said that research should be designed to sample across the domains to which the investigator will wish to generalize the results V. How Strong Are the Results? a. Significance Testing  The result that would be unlikely to appear if everything were due only to chance  Null hypothesis significance testing (NHST) attempts to answer the question o A difference between experimental conditions or a correlation coefficient that is calculated to be significant at the 5% level is different from 0 to a degree that, by chance alone, would be expected about 5% of the time o A difference or correlation significant at the 1% level is different from 0 to a degree expected by chance about 1% of the time, and so this is traditionally considered a stronger result o Calculate p-level probability level  Would give the probability of getting a difference of the size of that was found, if the actual size of the difference were to be 0 (null hypothesis) o Very difficult to describe logic precisely, and common descriptions are frequently wrong o Even if a “significant” result were one that probably did not occur by sheer chance, that would not necessarily mean that the result was strong or important o The criterion for a significant result is little more than a traditional rule of thumb  Why is a result of p 0  If the variables are negatively associatedcorrelation coefficient will be < 0  Interpreting correlations o Hard to understand o Need to understand the strength and usefulness of result  Binomial effect size display (BESD) Rosenthal and Rubin o How much of an effect an experimental intervention is likely to have o How well one can predict an outcome from an individual measurement of difference VI. Ethics a. The Uses of Psychological Research  Research raises ethical issues  Would findings do more harm than good? b. Truthfulness  Another ethical issue common to all research  Science is based on truth and trust  Scientific research is the attempt to seek truth in as unbiased a way as one can imagine c. Deception  Fundamental reliance of science on truth makes the use of deception in research worrisome  Why it should be allowed o Participants gave their “informed consent” to be deceived o The lies usually do no harm o Certain topics cannot be investigated without the use of a little deception VII. Tools of Exploration  Data are messages from the real world that can tell you what is really going on  Important to enhance reliability and validity of data to have any hope of using them to understand how the world works  Research methods are tools of exploration Chapter 5: I. The Nature of Personality Assessment  An individual’s personality consists of characteristic patterns of behaviour, thought, or emotional experience that exhibit relative consistency across time and situations  Patterns include many kinds of variables o Motives, intentions, goals, strategies, and subjective representations  All of these variables and many others are relatively stable attributes of the psychological makeup of individualsthey are all personality traits and any attempt to measure them involves personality assessment  Personality assessment is not restricted to psychologists, it is practiced by everyone  Personality traits are fundamental part of how we think about each other and ourselves  The most important thing to know about the personality assessment is the degree to which it is right or wrong o Evaluations of professional personality judgements or personality tests are said to appraise their validity o Evaluations of amateur judgements generally use the term accuracy o 2 basic criteria: agreement and prediction  Agreement: Does this judgement agree with other judgments obtained through other techniques or from other judges?  Prediction: Can this judgement of personality be used to predict behaviour or other life outcomes? II. The Business of Testing  The personality testers who distribute samples at the APA convention and those who hand out free so-called personality tests have a surprising amount in common: o Seeking new customers, using all the techniques in advertising, including free samples, to acquire them o Tests look superficially alike, they exploit a nearly universal desire to know more about the personality  However, the tests at the APA convention are well validated instruments that are useful for many purposes III. Personality Tests  Many personality tests are omnibus inventories: they were designed to measure a wide range of personality traits  Others are designed to measure just one trait a. S-Data Versus B-Data Personality Tests  Most personality tests provide S data o Ask you about what you are like, so the score you receive amounts to a summary of how you have described yourself o Shyness scale asks questions about how shy you are Objective o Attributional complexity scale asks about the level of complexity in your thinking tests about the causes of people’s behaviour  Whereas other personality tests provides B data o MMPI answers to these are informative about some aspect of personality Performanc o Impl
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