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Lecture 2

Lecture 2. Research Questions: Defining and Justifying Problems; Defining Hypotheses. Announcements:. SPSS installed on following PC’s: Upstairs lab Bisque Citron Crimson Ebony Ruby Olive Basement Lavender Sienna. Our Focus Today:. What makes a good research problem ?

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Lecture 2

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  1. Lecture 2 Research Questions: Defining and Justifying Problems; Defining Hypotheses

  2. Announcements: • SPSS installed on following PC’s: • Upstairs lab • Bisque • Citron • Crimson • Ebony • Ruby • Olive • Basement • Lavender • Sienna

  3. Our Focus Today: • What makes a good research problem? • Research Questions for Theory Development • Research Questions for Practical Application • Turning research problems into testable hypotheses

  4. Purpose of Research • To increase knowledge within a discipline or an area of study. • To increase knowledge as a consumer of research and to understand research within a discipline or area of study.

  5. Increasing Knowledge Within a Discipline or Area of Study • For Theory Development • Practical Application • Developing Research Tools

  6. Defining Research Problems • What is a problem? • “an interrogative sentence or statement that asks: What relation exists between two or more concepts?” • A problem can be restated in one or more ways to produce testable hypotheses. • A good research problem often produces more than one testable hypothesis.

  7. Characteristics of good research problems • Should state the concepts or variables to be related clearly and unambiguously • Should be testable • Should be feasible, given resources

  8. Three Specific Criteria for a Research Problem • What are we going to learn as the result of the proposed project that we do not know now? • Why is it worth knowing? • How will we know that the conclusions are valid?

  9. The Research Question • Common mistakes in defining research questions • Very broad area of interest • Too narrow • Cannot be measured • Problem is trivial or already understood

  10. Problem: Too Broad • Very broad area of interest • “I want to understand how people use the Internet” • “What factors influence the use of an interface?” • Solutions?

  11. Problem: Too Narrow • Too narrow • “Do Females Use Technology X more than Males?” • Solutions?

  12. Problem: Cannot be Measured • Cannot be measured • “Will this new information technology make society better?” • Solutions?

  13. Problem: Trivial or Previously Answered Research Questions • This is why we actually use literature– even in applied, business, or exploratory research. • Bringing an ‘old’ problem to a ‘new’ discipline is not necessarily trivial.

  14. So, what is a good research problem statement? • “The research problem is to investigate the presumed effect of A, B and C on X and Y in (population).

  15. Moving from General to Specific • “Could use of technology X affect society in a positive way?” • “If we looked at two populations, one using technology X and one not using it, would they differ?” • “How is the use of technology X related to productivity and work satisfaction in task groups within population Y?”

  16. Socioeconomic Status Academic Achievement Academic Ability Example from Week 1 Income Job Prestige Grades Level of Schooling attained Math skills Language skills

  17. Implications of Research Questions for Statistical Analysis

  18. Justification

  19. Justifying Research Problems • Explain what is not known about the problem. • Why does the problem matter? • Provide documentation that this is actually a problem. • Available statistics? • Available literature that shows that this is a needed area of inquiry?

  20. What is not a Justification? • No one has looked at it before. • Literature has failed to address the issue. • You think its interesting. • If it is ‘interesting’ then there is probably a justification buried in there, but you have to spell it out.

  21. Justification as Significance of the Study (Creswell 2003) • What are the ways that the study will add to the scholarly research/literature in the field? • How does the study improve practice? • How might the study improve policy?

  22. Turning Research Questions into Testable Hypotheses

  23. Inductive Logic of Research in Qualitative Studies Generalizations are made, or Theories to Past Experience And Literature Researcher Looks for Broad Patterns, Generalizations, or Theories from Themes or Categories Researcher Analyzes Data to Form Themes Or Categories Researcher Asks Open-Ended Questions of Participants Or Records Field Notes Researcher Gathers Information

  24. The Deductive Approach in Typical Quantitative Research Researcher Tests or Verifies a Theory Researcher Tests Hypotheses or Research Questions From the Theory Researcher Defines and Operationalizes Variables Derived from the Theory Researcher Measures or Observes Variables Using an Instrument to Obtain Scores

  25. Why not just rely on pure observation? • Subjectivity • “group A is nicer than group B” • Recall • What did you say to me last week about topic X? • Interpretations or conclusions that lack convincing support • “most kids don’t care what their parents say”

  26. Hypotheses • A good research question will produce one or more testable hypotheses. • Testable hypotheses predict a relationship between variables (not concepts).

  27. Three Basic Kinds of Hypotheses • Descriptive Questions • Single variable descriptions • Central tendency, variability, percentages • Associational • Non-directional relationship between variables. • Difference • Group Comparison

  28. Null hypothesis • Null Hypothesis: • H0: μ1 = μc • μ1is the intervention population mean • μc is the control population mean • In English… • “There is no significant difference between the intervention population mean and the control population mean”

  29. Alternative Hypotheses • Alternative Hypotheses: • H1: μ1 < μc • H0: μ1 > μc • H0: μ1 ≠ μc

  30. Alternative Hypotheses • Non-directional hypotheses • Associations, not causal • Directional • Increase in A increases B • Decrease in A decreases B • Inverse • Increase in A decreases B • Decrease in A increases B

  31. Conventions in Stating Hypotheses • Null hypothesis often not stated • Completely depends on convention in a given discipline • Three basic approaches to using variables in hypotheses: • Compare groups on an independent variable to see impact on dependent variable • Relate one or more independent variables to a dependent variable. • Describe responses to the independent, mediating, or dependent variable.

  32. Things to consider when stating hypotheses • Know what you want to explain: dependent variable • One common problem is under-specifying the key DV or DV’s • The independent variable(s) should have variation • Consider more than one independent variable, especially factors for which you might want to “control”

  33. Exploratory versus Confirmatory • Exploratory Research • Often just testing to see if there are associations between one or more variables. • Confirmatory Research • The more your topic has been researched, the more likely that you will be engaging in some type of confirmatory research.

  34. An Example Model Socioeconomic Status Academic Achievement Academic Ability

  35. Next Week: • Causation, Validity and Reliability • Read over the online “Layman’s Guide” to Research Methods

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