Chapter 3 Introduction to Quantitative Research

Based on the deductive model Quantity is the unit of analysis Amounts Frequencies Degrees Values Intensity Uses statistics for greater precision and objectivity

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Chapter 3 Introduction to Quantitative ResearchBased on the deductive modelQuantity is the unit of analysisAmountsFrequenciesDegreesValuesIntensityUses statistics for greater precision and objectivity1Copyright c 2001 The McGraw Hill Companies, Inc.Model for Conceptualizing Quantitative ResearchOverall purpose or objectiveResearch literatureResearch questions and hypothesesSelecting appropriate methodsValidity and reliability of the data2Copyright c 2001 The McGraw Hill Companies, Inc.Creating the Foundation for Quantitative ResearchConcept Abstract thinking to distinguish it from other elementsConstruct Theoretical definition of a concept; must be observable or measurableVariable Presented in research questions and hypothesesOperationalization Specifically how the variable is observed or measured3Copyright c 2001 The McGraw Hill Companies, Inc.Research Hypotheses for Quantitative Research Educated guess or presumption based on literatureStates the nature of the relationship between two or more variablesPredicts the research outcomeResearch study designed to test the relationship described in the hypothesis4Copyright c 2001 The McGraw Hill Companies, Inc.Quantitative Research HypothesesDirectional hypothesisPrecise statement indicating the nature and direction of the relationship/difference between variablesNondirectional hypothesisStates only that relationship/difference will occur5Copyright c 2001 The McGraw Hill Companies, Inc.Assessing HypothesesSimply stated?Single sentence?At least two variables?Variables clearly stated?Is the relationship/difference precisely stated?Testable?6Copyright c 2001 The McGraw Hill Companies, Inc.Null HypothesesImplicit complementary statement to the research hypothesisStates no relationship/difference exists between variablesStatistical test performed on the nullAssumed to be true until support for the research hypothesis is demonstrated7Copyright c 2001 The McGraw Hill Companies, Inc.Research Traditions in the Use of HypothesesHypotheses are always tentativeResearch hypothesis, not the null hypothesis, is the focus of the research and presented in the research report8Copyright c 2001 The McGraw Hill Companies, Inc.Research Questions in Quantitative ResearchPreferred when little is known about a communication phenomenonUsed when previous studies report conflicting resultsUsed to describe communication phenomena9Copyright c 2001 The McGraw Hill Companies, Inc.Types of VariablesVariable Element that is identified in the hypothesis or research questionProperty or characteristic of people or things that varies in quality or magnitude Must have two or more levelsMust be identified as independent or dependent10Copyright c 2001 The McGraw Hill Companies, Inc.Independent VariablesManipulation or variation of this variable is the cause of change in other variablesTechnically, independent variable is the term reserved for experimental studiesAlso called antecedent variable, experimental variable, treatment variable, causal variable, predictor variable11Copyright c 2001 The McGraw Hill Companies, Inc.Dependent VariablesThe variable of primary interestResearch question/hypothesis describes, explains, or predicts changes in itThe variable that is influenced or changed by the independent variableIn non-experimental research, also called criterion variable, outcome variable12Copyright c 2001 The McGraw Hill Companies, Inc.Relationship Between Independent and Dependent VariablesCannot specify independent variables without specifying dependent variablesNumber of independent and dependent variables depends on the nature and complexity of the studyThe number and type of variables dictates which statistical test will be used13Copyright c 2001 The McGraw Hill Companies, Inc.Intervening and Confounding VariablesIntervening variablePresumed to explain or provide a link between independent and dependent variablesRelationship between the IV and DV can only be explained when the intervening variable is presentConfounding variableConfuses or obscures the effect of independent on dependentMakes it difficult to isolate the effects of the independent variable 14Copyright c 2001 The McGraw Hill Companies, Inc.Operationalizing VariablesAll variables need an operationalizationMultiple operationalizations exist for most variablesSpecifies the way in which variable is observed or measuredPractical and useful?Justified argument?Coincides with the conceptual definition?15Copyright c 2001 The McGraw Hill Companies, Inc.Making the Case for Quantitative Research AdvantagesTradition and history implies rigorNumbers and statistics allows precise and exact comparisonsGeneralization of findingsLimitationsCannot capture complexity of communication over timeDifficult to apply outside of controlled environments16Copyright c 2001 The McGraw Hill Companies, Inc.Issues of Reliability and ValidityReliability = consistency in procedures and in reactions of participantsValidity = truth - Does it measure what it intended to measure?When reliability and validity are achieved, data are free from systematic errors17Copyright c 2001 The McGraw Hill Companies, Inc.Threats to Reliability and ValidityIf measuring device cannot make fine distinctionsIf measuring device cannot capture people/things that differWhen attempting to measure something irrelevant or unknown to respondentCan measuring device really capture the phenomenon?18Copyright c 2001 The McGraw Hill Companies, Inc.Other Sources of VariationVariation must represent true differencesOther sources of variationFactors not measuredPersonal factorsDifferences in situational factorsDifferences in research administrationNumber of items measuredUnclear measuring deviceMechanical or procedural issuesStatistical processing of data19Copyright c 2001 The McGraw Hill Companies, Inc.