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PSYC 1000 (740)
Chapter 2

Chapter_2_-_Studying_Behaviour_Scientifically[1].docx

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Department
Psychology
Course
PSYC 1000
Professor
Anne Bergen
Semester
Fall

Description
Chapter 2 – Studying Behaviour Scientifically Curiosity, skepticism, and open-mindness are driving forces behind scientific inquiry Diffusion of responsibility: each person feels decreased personal responsibility for intervening (ex: girl being raped when walking back to apartment, none of her neighbour call 911even though they knew what’s happening) Gathering Evidence: Steps in the Scientific Process 1) Initial Above example. Why did no one help? Observation/ Question 2) Form IF bystanders are present, THEN a diffusion of responsibility Hypothesis will decrease each bystander’s likelihood of intervening. (If- Then statement) 3) Test - create “emergency” in controlled setting Hypothesis by - manipulate perceived number of bystanders gathering - measure helping evidence 4) Analyze Data Helping decreases as the perceived number of bystanders increases. The hypothesis is supported. (if data do not support hypothesis, revise and retest) 5) Further Additional studies support the hypothesis.ATheory of Social Research and Impact is developed based on these and other findings. Theory Building 6) New The theory is tested directly by deriving a new hypothesis and Hypothesis conducting new research. Derived from Theory Hypothesis: tentative explanation or prediction about some phenomenon Theory: set of formal statements that explains how and why certain events are related to one another - Hindsight (after-the-fact) explanation is common method of trying to understand behaviour (living forwards, understanding backwards) - Hindsight explanation based on past events, which can be explained in many different ways, but they also provide chances so that further scientific inquiry can be built - Scientists want to understand the causes of a given behaviour so that they can predict and then control those conditions - Good theories generate an integrated network of predictions Characteristics of good theories: - organizes information in a meaningful way - testable - predictions made are supported by findings of new research - conforms the law of parsimony (simpler) - although scientists use prediction as a test of “understanding”, it doesn’t mean that prediction requires understanding Variable: any characteristics that can differ (ex: gender, age, ethnicity, school grades, etc) Operational definition: defines a variable in terms of specific procedures used to produce or measure it Self-report measures: ask people to report on their own knowledge, beliefs, feelings, experiences, or behaviour Social desirability bias: tendency of participants to give an answer that gives a good impression rather than one that reflects how they truly feel or behave Archival measures: past records which contain information about some type of behaviour Descriptive methods: involve recording observations or surveys Correlational methods: involve measuring the strength of an association between two or more events Experimental methods: involve manipulations to establish cause and effect relationships two or more events Case study: an in-depth analysis of an individual, group, or event Advantages of using case studies: - enable scientists to study and collect data when rare phenomenon occurs - may challenge validity of a theory or scientific belief - illustrate intervention programs to treat special populations Limitations on case studies: - poor method for determining cause-effect relations (ex: treatment causing infant’s weight gain) - generalization of the findings [may not be trustable] (ex: solution may only work for that person) - lack of objectivity in the way that researcher gathers and interprets data (ex: bias since different views) Naturalistic observation: way that researcher observes behaviour in a natural setting and tries to avoid influencing the participants when being observed Survey research: information about a topic is obtained by administering questionnaires or interviews to many people Key concepts of making a survey research: population and sample Population: consist of all individuals about whom we are interested in drawing a conclusion Sample: a subset of individuals drawn from the larger population of interest Representative sample: one that reflects the important characteristics of the population Random sampling: every member of the population has an equal probability of being chosen to participate in the survey Advantages of surveys: efficient method for collecting a large amount of information about people’s opinion and lifestyles Three drawbacks to surveys: - unrepresentative samples can lead to faulty generalizations about how an entire population would respond - rely on participants’self-reports (have to assume sample doesn’t lie) - cannot be used to draw conclusion about cause and effect Correlational research: research that measures two or more naturally occurring variables and examines whether they are statistically related (relation between X and Y) Correlation coefficient: statistic that indicates the direction and strength positively or negatively Positive correlation: higher scores on one variable are associated with higher scores on a second variable Negative correlation: higher scores on one variable are associated with lower scores on a second variable - correlation coefficient range from values of +1.00 to -1.00 (+/- represents direction) - zero correlation means X and Y are not related statistically Characteristics of an experiment: - researcher manipulates one variable - researcher measures whether this manipulation produces changes in a second variable - researcher attempts to control for extraneous factors Independent variable: factor that is manipulated by the experimenter Dependent variable: factor that is measured by the experimenter and may be influenced by the independent variable Experimental group: group that receives a treatment or
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