2. What is Descriptive Research Method also known as statistical research describes data and characteristics about the population or phenomenon the questions who, what, where, when and how a researcher cannot manipulate the variables under study

3. Fig 2.11 - Comparison of major research methods. This chart pulls together a great deal of information on key research methods in psychology and gives a simple example of how each method might be applied in research on aggression. As you can see, the various research methods each have strengths and weaknesses.

4. Descriptive Methods: Looking for Links Naturalistic observation Case studies Surveys Allow researchers to describe patterns of behavior and discover links or associations between variables but cannot imply causation Problems: research can’t describe what caused a situation cannot be used to create a causal relationship reader of the research will know what to do to prevent that disease

6. Naturalistic Observation a method of observation that involves observing subjects in their natural habitats Researchers take great care in avoiding making interferences using unobtrusive methods Advantage: ethically studies subjects who could not be experimented on Used where behavior is obvious

7. Naturalistic vs. Intrusive Intrusive: Should observers become actors with the subject Diane Fossey: Gorillas in the Mist – lived with gorillas AdvantageDisadvantage IntrusiveObservation is more accurate Presence changes outcome NaturalisticLess biasedToo removed to observe accurately

8. Case Studies an intensive study of a single group, incident, or community extreme case can be well-suited for getting a point across in an especially dramatic way critical case can be defined as having strategic importance in relation to the general problem researchers often use information-oriented sampling Not random sampling

9. Surveys A questionnaire or interview designed to investigate behaviors, attitudes, & opinions of a particular group Care-fully designed & use a sample Representative sample: closely resembles the population in age, sex, race, marital status & education level Random selection: every member of population has opportunity to be chosen Downside: requires complete honesty from subject

10. Fig 2.17 - The relationship between the population and the sample. The process of drawing inferences about a population based on a sample works only if the sample is reasonably representative of the population. A sample is representative if its demographic makeup is similar to that of the population, as shown on the left. If some groups in the population are over-represented or underrepresented in the sample, as shown on the right, inferences about the population may be skewed or inaccurate.

11. Correlation Studies Examines how closely 2 variables are related Can be used to analyze data brought in by other descriptive research methods Correlation does not indicate causality Valuable for: May rule out some factors & introduce others Can allow meaningful predictions

12. Fig 2.15 - Interpreting correlation coefficients. The magnitude of a correlation coefficient indicates the strength of the relationship between two variables. The sign (plus or minus) indicates whether the correlation is positive or negative. The closer the coefficient comes to +1.00 or –1.00, the stronger the relationship between the variables.

13. Correlation: Prediction, Not Causation Higher correlation coefficients = increased ability to predict one variable based on the other SAT/ACT scores moderately correlated with first year college GPA 2 variables may be highly correlated, but not causally related Foot size and vocabulary positively correlated Do larger feet cause larger vocabularies? The third variable problem

14. Fig 2.16 - Three possible causal relations between correlated variables. If variables X and Y are correlated, does X cause Y, does Y cause X, or does some hidden third variable, Z, account for the changes in both X and Y? As the relationship between smoking and depression illustrates, a correlation alone does not provide the answer. We will encounter this problem of interpreting the meaning of correlations frequently in this text.

15. Pitfalls of Descriptive Research Methods Observer interference: believe that anything being observed will be changed be what is observing it Sampling Bias – when the sample is not representative Distortions in self-report data: Social desirability bias – people wish to conform to what is seen as socially acceptable answers Response set – responding to questions in a way unrelated to what is being asked