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Theories of Personality Lecture 2

by: Kennedy Finister

Theories of Personality Lecture 2 PSYC 3570

Marketplace > Auburn University > PSYC 3570 > Theories of Personality Lecture 2
Kennedy Finister
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About this Document

research methods. case study, hypothesis. theories, validity. reliability
Theories of Personality
Elissa Hack
Class Notes
Psychology, Lecture Notes, class, Auburn University
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This 4 page Class Notes was uploaded by Kennedy Finister on Thursday August 18, 2016. The Class Notes belongs to PSYC 3570 at Auburn University taught by Elissa Hack in Fall 2016. Since its upload, it has received 38 views.


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Date Created: 08/18/16
Chapter 2 Lecture August 18, 2016 Personality Research Methods Outline • Hypothesis-testing approach • Case study method • Statistical analysis of data • Personality assessment The hypothesis testing approach Theories and Hypotheses • Theory: a general statement about the relationship between constructs or events o Can be very broad or very narrow o 2 things that make a good theory § Parsimonious: the simplest explanation is the best • So it can be generalized • A lot easier to test § Useful: hypotheses that can be tested. o NOT the thing that gets tested; the hypothesis is o Never Proven; just constanlt failed • Hypothesis: formal prediction about the relationship between two or more variables that is logically derived from theory • Replication and support Experimental Variables • Independent variable: o determines how the groups in the experiment are divided § Manipulated by the experimenter § Also known as the treatment variable § We have control over this • Dependent variable o measured by the investigator and used to compare experimental groups § Also known as outcome variable • Going to answer the question § Depends on what was manipulated Manipulated vs. Nonmanipulated Independent Variable Manipulated: • Begins with a large number of participants • Randomly assigns participants to experimental groups o So you’re able to make comparisons • Researchers assume that all the differences will be evened out Chapter 2 Lecture August 18, 2016 Nonmanipulated • Exists without the researcher’s intervention • Investigator does not randomly assign participants to a condition • Researcher cannot assume the people in the two groups are identical • Difficult to find cause-and-effect relationships o You need something to be manipulated to see these relationships Prediction vs. Hindsight • Accurate predictions can be made if a scientist has a legitimate theory. • Purpose of research is to provide support for a hypothesis Replication • Tests the research within a different population • Helps to determine whether an effect is generalizable • To increase accuracy and validity and to see consistency in results • File Drawer problem o Investigators publish and report research only when they find significant effects o Failed attempt at replication makes researcher to decide something has gone wrong § Leads research being stored in a file drawer and never reported The Case Study Method • In-depth evaluation of individuals o Observation & taking detail notes • A research records the person’s history, current behavior, and changes in behavior in great detail. o Done in psychotherapy, humanistic, & behavioral • Limitations o Generalization o Determining cause and effect § Nothing is being manipulated o Subjective judgments § Huge issue in Freud’s work § Bias towards the answer you want • Strengths o Offers specific insight into an individual’s life § Get info we couldn’t get if we test a large group o Can generate new hypotheses o Appropriate for rare cases o Gives insight to treatments Chapter 2 Lecture August 18, 2016 § If it works with one person it could work for another. Gives a starting point for psychologists o Demonstrate possibilities Statistical Analysis of Data Statistical Significance • The difference between two averages is large enough to consider that it was not cause by chance but reflects a true difference between two observations o P value § Must be less thanà .05 • There is less than 5% that this was caused by chance • 95% certainty that this was result of manipulation • bigger the sample size easier it is to get in the 5% range o Effect size § General indicator of how important that p-value is Correlation Coefficients • Statistical test that helps understand the relationship between two measures o How they correspond to each other. NOT SHOW CAUSE AND EFFECT • Statistical data is reduced to a single number that ranges from 1.00 to -1.00 o Sign doesn’t matter for strength. Just depends how close it is to 1 or -1 Personality Assessment Reliability • The extent to which a test measures consistently o Same score test after test • Calculated using test-retest reliability coefficient • Could be affected by vague questions or scoring, or test taker's mood • Internal consistency o Make sure all questions are related to the topic or what you were trying to figure out Validity • The extent to which a test measures what it was designed to measure o Face validity § Test looks like its testing what its testing § Questions received correspond with what you’re testing o Congruent validity § Does it highly correlate with other tests measuring the same thing? o Discriminant validity § Tests should have very low correlation with tests looking for something completely different Chapter 2 Lecture August 18, 2016 o Behavioral validation § Tests predict behavior § Example: • If they score high on extraversion on a personality test then they should be extraverted in the “future” **A TEST CAN BE RELIABLE & NOT VALID**


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