SCIENCE

1. SCIENCE • naturalistic explanation • all explanation is of nature, in terms of nature • allows no entities that have powers beyond other entities, that are not subject to determinism, that are uncaused or otherwise unique • our view of nature: scientific materialism • only matter in motion exists • view of nature resulting from 17th century science

2. SCIENCE AS METHOD • systematic empirical observation • guided by theory to reveal something about world • theory is set of testable propositions • has implications for observation • organizes past observations • guides future observations • focuses on solvable problems • publicly observable data • replication by others using method info • peer review in journals

3. DETERMINISM

4. Is Science the Only “True” Way of Knowing the World? NO Sometimes, we are all guided by authority figures. Sometimes, we just use common sense to get around in the world Sometimes, we accept truths on the basis of belief or faith alone BUT, science is based on direct observation and empirical testing.

5. The science of Psychology seeks to 1. Describe behavior 2. Predict behavior 3. Understand behavior 4. Change behavior How does it accomplish these aims? --by using the Scientific Method From Zechmeister et al. text

6. Goals of Science Describe Predict Understand Control Scientific Method (deductive thinking) world of concepts Theory Prediction Revision (inductive thinking) “real” world Observation Verification

7. (deductive thinking) world of concepts Theory Prediction Revision (inductive thinking) “real” world Observation Verification Where do Methods & Statistics Fit? Methods Correlational Experimental Statistics Hypothesis Testing

8. Steps of the Scientific Method 1. Develop a research question 2. Generate a research hypothesis 3. Form operational definitions 4. Choose a research design 5. Evaluate the ethics 6. Collect data 7. Analyze data and form conclusions 8. Report research results These steps are used in both basic and applied research

9. Cyclical Process Report the Results Define the Question Analyze the Data Design the Study Collect the Data

10. Some Terminology • experiment vs. correlational study • IV vs. DV • constructs and operational definitions • sample vs. population • statistic vs. parameter • descriptive vs. inferential statistics • Ho vs. Ha (hypotheses) • Type I vs. Type II error • continuous vs. categorical variables • scales of measurement • reliability and validity

11. Experiment -- involves random assignment of participants and control over the research situation to minimize the influence of other variables and highlight the causal effect of the manipulation. Correlational Study -- examines direction and strength of relationship between variables; no cause implied. Independent variable -- the one manipulated by the experimenter (cause). Dependent variable -- the one measured by the experimenter (effect). Descriptive Statistics -- statistics and methods for organizing and summarizing data. Inferential Statistics -- techniques to permit inferences or generalizations from samples to the populations from which they were drawn (Statisticis to sample as Parameter is to population.)

12. Scales of Measurement • nominal: assign labels to categories • ordinal: assign order to categories • interval: ordinal, and includes equal distances • ratio: interval, and includes an absolute zero

13. Scales of Measurement • nominal: car color, sex, religion, ethnicity • ordinal: reading grade level; exam finishing order • interval: Fahrenheit temperature; IQ, SAT (?) • ratio: Kelvin temperature; height; reaction time

14. Reliability • The consistency or repeatability of a measure • The degree to which a measure would give you the same result over and over, assuming the phenomenon being measured is not changing • Cannot be calculated, only estimated • [Based on true score theory of measurement (Trochim pp. 60-72)]

15. Construct Validity Construct validity is the approximate truth of the conclusion that your operationalization accurately reflects its constructs. Central questions to ask are: • “Is your operationalization an accurate translation of the construct?” • “Does your program/treatment accurately reflect what you intended?” • “Does your sample accurately represent your idea of the population of interest?” • “Are you measuring what you intended to measure?”

16. Random Selection and Random Assignment • Random selection is how you draw the sample of people for your study from a population—impacts external validity. • Helps insure that the sample is representative of the population (and hence, findings are moregeneralizable) • Random assignment is how you assign the sample to different groups or treatments in your study—impacts internal validity. • Helps insure that groups are comparable at the beginning of the study

17. Internal Validity • “The approximate truth about inferences regarding cause-effect (causal) relationships” (Cook & Campbell,1979) • The primary consideration in establishing cause and effect • Key question: Can observed changes (effect) be attributed to the program or intervention (cause) and not some other possible (alternative) cause? • Only relevant to the specific study in question (i.e., is not concerned with generalizability)

18. Reliability and Validity