1. Scientific Inquiry

2. What is Scientific Inquiry Scientific inquiry is the system or procedure by which we seek to understand and explain behavior or the world around us

3. Science vs Pseudoscience

4. Canons of Science Deterministic –events have meaningful causes Empiricism –Good and bad ways to determine cause and effect –Making observations Law of Parsimony (Occam’s Razor) –If two explanations are equally good, choose the simpler one

5. Canons of Science Scientific theories must be: –Testable –Falsifiable Define the circumstances under which your theory is wrong –Repeatable Given the same set of circumstances, the same outcome should occur across observations

6. The Scientific Process We make observations about a specific behavior We develop a theory to account for the behavior We come up with a hypothesis based on our theory –If my theory is true under this situation, then X should happen –If, under this situation, X does not happen, then my theory is false

7. The Scientific Process We conduct a controlled test of our hypothesis We gather objective data –We define the variables of interest We analyze the results We accept or reject our hypothesis

8. Pseudoscience What is it? –Presenting something as fact without sufficient scientific evidence –Not testable How do we recognize it? –Use of scientific-sounding terms (e.g., quantum; vibrational) –E.G., ESP, Penta Water, Accupuncture, Homeopathy, Feng Shui,

9. The Scientific Method Good Science

10. We make observations –We observe and describe behavior or event –E.G., A man, who was leaving a bar, crashes into a parked car on the way home

11. Good Science We develop a theory to explain the behavior or event –What theories can you come up with to account for this behavior and/or outcome? He was drunk Drunk driving causes accidents Alcohol causes impairment of driving abilities Talking on cell phones causes accidents (was he on a cell phone?) The brakes on the car malfunctioned The Flying Spaghetti Monster hates people who drive after leaving bars

12. The Flying Spaghetti Monster Taken from: www.venganza.org

13. Good Science We come up with a hypothesis based on our theory –Remember: a good theory must generate hypotheses that are testable and falsifiable –We must be able to operationally define the variables of interest

14. Good Science Operational Definitions –Define, concretely, how you will measure the variables of interest

15. Good Science Theory 1: The flying spaghetti monster hates people who leave bars and drive –Hypothesis: If you leave a bar and drive, the Flying Spaghetti Monster will hate you and therefore cause you to get into an accident

16. Good Science Theory: Alcohol impairs driving ability –Hypothesis 1: People who drink alcohol are more likely to get into car accidents than those who do not drink alcohol –Hypothesis 2: Alcohol slows down reaction time which causes more accidents –Hypothesis 3: Alcohol increases risk-taking while driving which causes more accidents

17. Good Science Which of these hypotheses is –testable? –repeatable? –falsifiable Can we operationally define the variables of interest? Hypothesis: If you leave a bar and drive, FSM will hate you and cause you to have an accident Hypothesis: Alcohol slows down reaction time which causes more accidents

18. Good Science So, which Hypothesis should we test? Hypothesis: If you do leave a bar and drive, He will hate you and cause you to have an accident Hypothesis 1: Alcohol slows down reaction time which causes more accidents

19. Good Science We conduct a controlled test –We select a research design –We identify the population and select a sample –We define the variables of interest

20. Research Design Non-experimental vs Experimental designs –Non-experimental – observe a single group of subjects at one point in time Observational studies Survey Studies –Experimental – involves multiple groups or multiple observations across time Control – standard against which the effects of the experimental condition is compared

21. Research Design External Validity –Can we generalize our findings from the experimental context to other people, in other places, at other times?

22. External Validity Random Sampling –Identify Population All people All adults All adults who drink alcohol All adults who drive after drinking alcohol –Select Sample Select sample from population of interest –Random –Stratified – representative of the population on key characteristics

23. External Validity

24. Research Design Internal Validity –Can we be confident that the observed outcomes are due to (caused by) our experimental treatment and NOT to some other cause?

25. Internal Validity In our study, we put all of the heavy drinkers in the group that received alcohol and all of our light or non-drinkers in the group that received water To help subjects “get in the mood,” the bartender played loud and upbeat music during the “drink alcohol” condition. No music was played during the “drink water” condition.

26. Research Design Random Assignment –Place subjects at random into different control and experimental conditions –Goal is to ensure that potential confounds are equally represented in both groups Confound – uncontrolled and/or unmeasured characteristic(s) that accounts for the observed findings –Not always possible, so how do we ensure internal validity?

27. Testing Hypotheses Observation – a man leaves a bar and gets into a car accident –Hypothesis 1: Heavier drinkers take more risks while driving than lighter drinkers –Hypothesis 2: Individuals who are intoxicated take more risks while driving than individuals who are sober

28. Testing Hypotheses Independent variable –Predictor Variable –Variable that is manipulated Dependent Variable –Predicted variable –Variable that “depends on” or is affected by the independent variable Operational definition –Concrete description of how your variables will be measured

29. Testing Hypotheses Hypothesis 1 –IV: level of drinking is defined using the quantity frequency index –DV: Risk-taking is defined as frequency of speeding (i.e., number of days per week that the individual drives 10 + miles over the speed limit) Frequency of tailgating

30. We analyze the data and reject or accept our hypothesis

31. Statistical Analysis

35. Variance Explained

36. Pirates and Global Warming

37. Testing Hypotheses Hypothesis 2 –IV: Intoxication is defined as a BAC of.08 mg% or greater –DV: Risk-taking is defined through use of a simulated driving task as amount of time spent speeding and number of times passing cars on a double yellow line

38. Statistical Analysis

40. Good Science A theory becomes a law when –supporting evidence accumulates over multiple tests of the associated hypotheses and –it has never been proven false –E.g., the law of physics Pseudoscientific claims cannot become laws

41. Ethical Issues Informed Consent –Subjects must be fully informed about Potential risks and benefits of participation Exactly what the study involves –Deception Deception can be used if necessary to test hypotheses Participation is voluntary Coercion is not acceptable