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

WHAT IS RESEARCH ALL ABOUT, ANYWAY? Increasing our understanding of how and why we behave the way we do!!

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

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

DEPENDENT VARIABLES (DVs) The Outcomes of a Research Study Depends on the experimental treatment

INDEPENDENT VARIABLES (IVs) Treatments or conditions under control of the researcher Levels—at least two different values of the IV must be present

INDEPENDENT VARIABLES IN FACTORIAL DESIGNS

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

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

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

HYPOTHESIS Reflects the general problem under study Restates the general problem in a form that is precise enough to allow testing

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

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

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

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

PURPOSE OF RESEARCH HYPOTHESIS Directly tested during research process To compare against Null hypothesis

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

WHAT MAKES A GOOD HYPOTHESIS? Stated in declarative form Posits a relationship between variables Reflects theory or literature Brief and to the point Testable

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

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