Terminology ReviewConcept reviewVariablesSlide 4Slide 5Slide 6Slide 7Slide 8Levels of MeasurementTypes of input or treatmentTypes of output or outcome measureNumber of outcomesExperimental vs. Non-ExperimentalTypes of research designsTypes of research designsSlide 16Statistics ReviewMeasures of central tendency and dispersionSlide 19Slide 20Slide 21Slide 22Relationships between variablesBoth Variables ContinuousSlide 25Discrete predictor, continuous outcomeDiscrete predictor, continuous outcomeHypothesis Testing and ZSlide 29Power and ZSlide 31Slide 32Slide 33Terminology ReviewTerminology ReviewPsy 420Psy 420Andrew AinsworthAndrew AinsworthConcept reviewConcept reviewResearch TerminologyResearch TerminologyVariablesVariablesIVs and DVs IVs and DVs •Independent variables Independent variables are controlled by the experimenter are controlled by the experimenter and/orand/or are hypothesized to influence other variables (e.g. are hypothesized to influence other variables (e.g. DV) DV) and/orand/or represent different groups or classifications represent different groups or classifications participants belong to (either assigned or ascribed)participants belong to (either assigned or ascribed)•Dependent variables are what the participants are Dependent variables are what the participants are being measured on; the response or outcome variablebeing measured on; the response or outcome variable•Think of them as “input/output”, “stimulus/response”, Think of them as “input/output”, “stimulus/response”, etc.etc.•Usually represent sides of an equationUsually represent sides of an equationVariablesVariablesQualitative vs. QuantitativeQualitative vs. Quantitative•Qualitative variables are those that change Qualitative variables are those that change in quality or kind in quality or kind (e.g. male/female, ethnicity, etc.)(e.g. male/female, ethnicity, etc.)•Quantitative variables are those that change Quantitative variables are those that change in amountin amountVariablesVariablesContinuous, discrete and dichotomousContinuous, discrete and dichotomous•Continuous data Continuous data smooth transition from one to the other rather smooth transition from one to the other rather than in steps, than in steps, can take on any value in a given range can take on any value in a given range the number of given values in the range are only the number of given values in the range are only limited by the precision of the measuring limited by the precision of the measuring instrument (can be infinite)instrument (can be infinite)VariablesVariablesContinuous, discrete and dichotomous Continuous, discrete and dichotomous •DiscreteDiscreteCategoricalCategoricalLimited amount of valuesLimited amount of valuesAnd always whole values And always whole values •DichotomousDichotomousdiscrete variable with only two categoriesdiscrete variable with only two categoriesVariablesVariablesContinuous, discrete and dichotomousContinuous, discrete and dichotomous•Continuous to discreteContinuous to discreteoften for the sake of simplicity continuous data is often for the sake of simplicity continuous data is “dichotomized”, “trichotomized”.“dichotomized”, “trichotomized”.Often because people are obsessed with anovas Often because people are obsessed with anovas or some other stat they are accustomed to (chi-or some other stat they are accustomed to (chi-square, etc.)square, etc.)Doing this will reduce your power and cloud Doing this will reduce your power and cloud your interpretation your interpretation Reinforce use of the appropriate stat at the right Reinforce use of the appropriate stat at the right timetimeVariablesVariablesContinuous, discrete and dichotomousContinuous, discrete and dichotomous•Which type of data you have will decide what type Which type of data you have will decide what type of analysis you should or at least can useof analysis you should or at least can use•Much of the differences in the chapters in this Much of the differences in the chapters in this book have to do with what kind of data your book have to do with what kind of data your dealing with (plus how it’s collected and other dealing with (plus how it’s collected and other things)things)Levels of MeasurementLevels of MeasurementNominal – CategoricalNominal – CategoricalOrdinal – rank orderOrdinal – rank orderInterval – ordered and evenly spaced; changes in the Interval – ordered and evenly spaced; changes in the construct represent equal changes in what you are construct represent equal changes in what you are intended to measureintended to measureRatio – has absolute 0; a true absence of the trait.Ratio – has absolute 0; a true absence of the trait.•y(I, R) – one sample t-testy(I, R) – one sample t-test•y(O, N) – one-way chi-squarey(O, N) – one-way chi-square•y(I, R) and x(O, N) – two sample inde. t-test, one-way ANOVAy(I, R) and x(O, N) – two sample inde. t-test, one-way ANOVA•2 xs (O, N) – two-way chi square2 xs (O, N) – two-way chi square•The last two are usually grouped together and treated as The last two are usually grouped together and treated as “continuous”.“continuous”.Types of input or treatment Types of input or treatment Qualitative input – sex (male/female), Qualitative input – sex (male/female), ethnicity, treatment groups, etc.ethnicity, treatment groups, etc.Quantitative input – age groups, weight Quantitative input – age groups, weight classes, years of education, etc. These can be classes, years of education, etc. These can be quantitative categories (e.g. ANOVA) or quantitative categories (e.g. ANOVA) or continuous predictors (e.g. regression).continuous predictors (e.g. regression).Types of output or outcome measureTypes of output or outcome measureOutput variables can also be discrete, ordinal or Output variables can also be discrete, ordinal or continuous.continuous.Research using continuous outcome measures will be Research using continuous outcome measures will be the focus of this class. the focus of this class. •These outcomes measure the amount of something and also These outcomes measure the amount of something and also track the degree the amount changes between groups or time track the degree the amount changes between groups or time periods.periods.Analyses of discrete or ordinal data is