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CORRELATIONAL RESEARCH

CORRELATIONAL RESEARCH. Asks what several events have in common Asks whether knowing one event can allow prediction of another event Does not imply causation. -When research shows that two traits are connected together -If one trait is there, the other is too. Correlation.

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CORRELATIONAL RESEARCH

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  1. CORRELATIONAL RESEARCH • Asks what several events have in common • Asks whether knowing one event can allow prediction of another event • Does not imply causation

  2. -When research shows that two traits are connected together -If one trait is there, the other is too Correlation Module 4: Research Strategies

  3. When one trait is strong, the other is too Positive Correlation

  4. If one trait is strong, the other is weak Negative Correlation

  5. There is no relationship at all between the two traits. Zero Correlation

  6. However, correlation is NOT causation • One trait does not cause the other Hair color does not CAUSE eye color Blue Green Brown Eye Color Blonde Brown Red Hair Color

  7. Experiment • A research method in which the researcher manipulates and controls certain variables to observe the effect on other variables. • Hypothesis- a testable prediction about the outcome of research

  8. Design an experiment for each of these ideas. • Playing sports makes a person more/less aggressive • Women are more/less friendly than men • Teenagers have more/less emotional problems than adults • People become friends with others who are similar/different from themselves. Activity:

  9. Experimental Research – highest constraint “True Experiment” Control: Systematic methods Reduce threats to validity Limit Extraneous variables (confounds)  RANDOM ASSIGNMENT • Measurement procedures carefully designed and precisely followed

  10. Variables

  11. Variable - A behavior or cause of behavior that is studied through experiments

  12. Independent Variable (IV): The variable that a researcher changes Each group is given a different variable …”I” do the research…it’s what “I” control

  13. Independent Variable Example 1: Group 1 gets 100mg of a drug Group 2 gets 25mg Group 3 gets a fake pill Here the IV is DRUG (different amounts) IV 25 mg 100 mg Sugar pill

  14. Example 2: Either give some subjects 20, 60 or 40 watts and test their performance on a math test 20 watts 60 watts 100 watts The IV = the amount of light

  15. Dependent Variable: -The variable that changes because the researcher changed the IV -The variable that you measure

  16. Dependent Variable Example 1: Group 1 gets 100mg of a drug --- Sleeps for 9 hours Group 2 gets 25mg – Sleeps for 4.5 hours Group 3 gets a fake pill – Sleeps for 1 hour Here the DV is sleep (different amounts) IV 25 mg 100 mg Sugar pill

  17. Example 2: Either give some subjects 20, 60 or 40 watts and test their performance on a math test 20 watts 60 watts 100 watts The DV = the different test scores

  18. Dependent Variable: Reaction time cancer cells errors on memory test

  19. Types of Research = (approach to gathering data) LOW • Nonscientific • Naturalistic Observation • Case Study • Correlational Research • Quasi-experimental Research • Experimental Research Level of Constraint HI HI Level of Constraint: More control = more precision

  20. Non Scientific: ex: Historians

  21. CONSTRUCTS: Inferences we make memory Super ego ego id personality Reification of a construct: logical error when we confuse a fact with a construct

  22. An unexpected (confounding) variable??

  23. Confounding Variables

  24. The only thing that should change in an experiment is the independent variable. If something else changes during the experiment, it is a confounding variable

  25. Confounding = confusing; causing problems Confounding Variables -Any variable that is different for the two groups of subject -It might change the results of the study

  26. Examples of Confounding Variables: • Different environments • Room color • Temperature, seat comfort • Loudness • Sample is not random • Researcher treats the groups differently • Helps one group more • Is nicer to one group • Subjects know the experiment and hypothesis

  27. examples of confounding variables testing subjects on a memory test …temperature in the room is HOT …impact on the tests results Examining the effects of alcohol on driving and obeying posted signs…but you don’t test their eyesight

  28. Life Expectancy

  29. Figure 5-1. (p. 106)Graphical representation of the data in Table 5-3 showing the characteristic pattern of(a) high positive correlation, (b) essentially zero correlation, (c) strong negative correlation.

  30. TRUE EXPERIMENTAL RESEARCH • Sample is assigned to groups • The surrounding is controlled by researcher

  31. Experimental Design

  32. Schizophrenia and semantics

  33. In an experiment, a variable other than the independent variable that could produce a change in the dependent variable • The variable “confounds” the results Confounding Variable

  34. Experiments: Control for Other Confounding Variables Module 4: Research Strategies

  35. Any differences in the experiment’s conditions--between the experimental and control groups • Differences include temperature, lighting, noise levels, distractions, etc. • Ideally, there should be a minimum of environmental differences between the two groups. Confounding Variables: Environmental Differences

  36. Any changes in an experiment’s results due to the subject anticipating certain outcomes to the experiment Confounding Variables:Expectation Effects

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