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Chapter 2

Chapter 2 + Appendiz B.docx

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Wilfrid Laurier University
Mindi Foster

Chapter 2 + Appendix B Empirical research via Experimental Design st  1 step – start with a theory in order to derive a hypothesis (a coherent network of ideas) from it. the hypothesis must be testable and we do this via good, operational definitions. o Goal one: measurement, Goal two: prediction. o A good operational definition is the act of the operation we use to measure the components/variables of the hypothesis o ex. Pets are important for a good life = theory; pet owners experience less stress the non pet owners = hypothesis o You do not measure one thing at one time  2 Step – Design the study o a variation in the type of study you can perform: Experimental, Descriptive/Correlational  Step 3 – collect data  Step 4 – perform statistics o Analysis data o Hypothesis testing  Step 5 o Publish the data/ report the finidings  If this fails, we need to critically evaluate the design, hypothesis, etc. to revise Experimental Design Hypothesis (pet owners experience less stress) Dependent variable (what is Independent variable (what measured as a function of the experimenter varies/manipulates/causes the IV) to happen) Our Y, the effect Our X, the cause Control condition (absence of the IV). Allows us to Experimental Condition compare the individuals for whom did not receive (the presence of the IV) the independant variable. Must be as similar to the experimental condition as possible, except the independant variable so that the only difference between them is the independant variable via Random assignment: participants have equal chance of being assigned to either experimental or control condition. So we create an equal playing field across the two conditions Example: TV watching Hypothesis: Lots of tv watching results in death/ heart disease/diabetes Independent variable: Dependent variable: TV watching Outcome, the measure of heart disease, diabetes, Our X, the cause and death Our Y, the effect Control condition: Must be as similar to Experimental Condition: the experimental condition as possible, Participants are made to except the independant variable so that watch 3 hours of the only difference between them is the television independant variable Experiments provide inference of Causation  Manipulation of X  Control of other variables (Control condition, Random assignment, operation definitions How does random assignment creates this equal playing field by reducing:  extraneous variables (variables other than the IV that may influence the DV) o Ex. TV  bad health  The type of TV  Eating junk food and watching TV at the same time  Pre-experimental health  Family history o Studying  leads to good grades  Attention span  Liking the subject  Prior knowledge  Better memories  Higher IQ  confounding (when extraneous variables and IV cannot be teased apart)? o If there are too many extraneous variables o Cannot conclude that the IV  DV Non Random Assignment: Does Studying lead to good grades? 7A 7D Experimental Control Participants Studying No Studying Individual 1: High IQ 11: Low IQ Individual 2: High IQ 12: Low IQ Results A’s F’s Extraneous variable = IQ; IQ is confounding the effect of studying on good grades Random Assignment – No division based on IQ, randomly assigning individuals a number; we have equal numbers of our extraneous variable scattered across the groups/conditions. Everyone through random assignment had an equal chance of being assigned to either condition. Experimental Control Participants Studying No Studying Individual 1: Low IQ 11: High IQ Individual 2: High IQ 12: Low IQ Results A’s F’s We have equal amounts of the extraneous variables in each group. Therefore, the groups are equalized on everything with the exception of the IV. Between- subjects design  Comparing two groups; giving one person one condition, One independent variable Exp. Control P 1 P4 P2 P5 P3 P6 Types of Experiments  Within subjects design – comparing the outcome within people; giving one person 1 person 2 conditions Experimental Control P1 P1 P2 P2  Factorial Design
 - more then one independent variable o Interaction between two independent variable. o Occurs when the effect of one independent variable on the dependent variable 
 depends on the effect of the other o Ex. How the amount of studying (IV) affects enjoyment of uni (DV) High Studying (Exp) Low Studying (Control) Low High Unliked Course Enjoy Enjoy High Low PS 101 enjoy enjoy  The effect on the amount of studying on enjoyments depends in the type of course  Multivariate Designs (repeated measures)- more then one dependent variable Ex. 3 types 1) diabetes, 2) heart disease, 3) Dealth Or repeating some variable many times Advantages/Disadvantages of Experiments  cause/effect – manipulate, control all else; therefore IV  DV  decreased external validity o how the lab results generalize outside to real world  inappropriate for certain variables o you cannot manipulate certain things  ex. Gender, ethnicity Empirical research via Descriptive/Correlational designs Types:
  Naturalistic observation (observing behavior without intervening) o Because we have not manipulated a variable we can only say that they are related and not one cause of another o Ex. Do red cars go faster then others  Case study (in-depth investigation of an individual subject) o But generalize on one person’s data  Surveys (gathering information about specific aspects of people’s behavior) o Ex. Mass testing Advantages/Disadvantages
 Advantages  Lots of information that cannot be controlled in experiments can be gathered Disadvantages  lack of causality, due to confounding o manipulated X  Y; might find a relationship between X and Y that is not a causal relationship but a correlation  ex. There is a correlation between the number of appliances you have
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