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CHAPTER OVERVIEW All About Variables The Relationship Between Independent and Dependent Variables Other Important Types of Variables Hypotheses Samples and Populations The Concept of Significance
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WHAT IS RESEARCH ALL ABOUT, ANYWAY? Increasing our understanding of how and why we behave the way we do!!
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THE RESEARCH PROCESS: COMING TO TERMS From Problem to Solution –Noting an interesting question –Stating the question in such a way that it can be answered The Language of Research
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VARIABLES A class of outcomes that can take on more than one value The more precisely a variable is measured, the more useful the measurement is
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DEPENDENT VARIABLES (DVs) The Outcomes of a Research Study Depends on the experimental treatment
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INDEPENDENT VARIABLES (IVs) Treatments or conditions under control of the researcher Levels—at least two different values of the IV must be present
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INDEPENDENT VARIABLES IN FACTORIAL DESIGNS
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THE RELATIONSHIP BETEWEEN INDEPENDENT AND DEPENDENT VARIABLES: WHAT MAKES GOOD VARIABLES? Independent Variable is not confounded –Levels do not vary systematically with other variables Dependent Variable is sensitive to changes in the IV
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OTHER IMPORTANT TYPES OF VARIABLES Control Variable—Has a potential influence on the DV Extraneous Variable—Has an unpredictable impact on the DV Moderator Variable—Variables related to IVs and/or DVs, and hiding the true relationship between IVs and DVs
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VARIABLES—A SUMMARY Type of Variable DefinitionOther Terms You Might See Dependent A variable that is measured to see whether the treatment or manipulation of the independent variable had an effect Outcome variable Results variable Criterion variable Independent A variable that is manipulated to examine its impact on a dependent variable Treatment Factor Predictor variable Control A variable that is related to the dependent variable, the influence of which needs to be removed Restricting variable Extraneous A variable that is related to the dependent variable or independent variable that is not part of the experiment Threatening variable Moderator A variable that is related to the dependent variable or independent variable and has an impact on the dependent variable Interacting variable
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HYPOTHESIS Reflects the general problem under study Restates the general problem in a form that is precise enough to allow testing
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NULL HYPOTHESIS States that there is no relationship between the independent and dependent variables under study H o : µ 1 = µ 2 –H o : Null hypothesis –µ 1 : Theoretical average of population 1 –µ 2 : Theoretical average of population 2
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PURPOSE OF NULL HYPOTHESIS A starting point for analysis –Accepted as true absent other information –Assumes that chance caused any observed differences Provides a benchmark for comparison
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THE RESEARCH HYPOTHESIS A statement of inequality A relationship exists between the independent and dependent variables H 1 : ≠ –H 1 : Research hypothesis – : Theoretical average of population 1 – : Theoretical average of population 2 X1X1 X2X2 X1X1 X2X2
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DIRECTIONAL VS. NONDIRECTIONAL RESEARCH HYPOTHESES Nondirectional Research Hypothesis –Groups are different, but direction is not specified –H 1 : ≠ Directional Research Hypothesis –Groups are different, and direction is specified –H 1 : > –H 1 : < X1X1 X1X1 X2X2 X1X1 X2X2 X2X2
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PURPOSE OF RESEARCH HYPOTHESIS Directly tested during research process To compare against Null hypothesis
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Research –Inequality between variables –Refers to sample –Directly tested –Stated using Roman symbols ( ) –Explicit DIFFERENCES BETWEEN NULL AND RESEARCH HYPOTHESES Null –Equality between variables –Refers to population –Indirectly tested –Stated using Greek symbols (µ) –Implied X
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WHAT MAKES A GOOD HYPOTHESIS? Stated in declarative form Posits a relationship between variables Reflects theory or literature Brief and to the point Testable
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SAMPLES AND POPULATIONS The SAMPLE is a representative portion of a POPULATION The POPULATION is the entire group of interest Results from the SAMPLE should generalize to the POPULATION
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SIGNIFICANCE Observed differences (PROBABLY) result from the treatment and not from chance Why? –Influences other than the treatment Significance level = risk associated with not being 100% certain that Null hypothesis is incorrect
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