1 / 22

Research Design

Research Design. What is Research Design ?. Plan for getting from the research question to the conclusion Blueprint for data collection and interpretation Deals with the logic of scientific inquiry A strategy for testing hypothesis Interpretative work Understanding phenomenon

ciaran-shaw
Download Presentation

Research Design

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Research Design

  2. What is Research Design ? • Plan for getting from the research question to the conclusion • Blueprint for data collection and interpretation • Deals with the logic of scientific inquiry • A strategy for testing hypothesis • Interpretative work • Understanding phenomenon • A plan for conducting scientific research for the purpose of learning about a phenomenon of interest

  3. What is Research Design ? • Overall plan or framework for the investigation, anticipate all of the subsequent stages of the research process. • Decision also be made for: • Selecting unit of analysis • Selecting variable to observed and controlled • How to measured variables • How to analyze of data • Good Research Design should rule-out alternative explanations

  4. Alternative Explanations • Asian financial crisis in the late 1990’s • Institutional weaknesses (lack of transparency in corporate and political governance) -> cronyism • Market failure with under-regulation of financial market

  5. Unit of Analysis • The entity about whom or which the researcher gathers information. • The unit is simply what or who to be described or analyzed • Examples of unit: • Individuals • Groups • Artifacts (books, photos, newspapers) • Geographical units (town, census tract, state) • Social interactions (dyadic relations, divorces, arrests)

  6. Units of Analysis Examples • If you are comparing the children in two classrooms on achievement test scores, the unit is the individual child because you have a score for each child. • On the other hand, if you are comparing the two classes on classroom climate, your unit of analysis is the group, in this case the classroom, because you only have a classroom climate score for the class as a whole and not for each individual student.

  7. Units of Analysis Examples (2) • If the researcher wanted to know what kind of people are attracted to the field of computer science, the unit is individual people • If the researcher wanting to determine if larger organization have more bureaucratic rules and regulations, the unit is organization

  8. Hierarchical Modeling • The incorporation of multiple units of analysis within a single analytic model • Aggregation in the analysis • Analyze individual person using aggregate data to characterize the groups or collectivities to which the individuals belong. • For instance, in an educational study, you might want to compare student performance with teacher expectations. To examine this relationship would require averaging student performance for each class because each teacher has multiple students and you are collecting data at both the teacher and student level.

  9. Fallacy • An error in reasoning, usually based on mistaken assumptions. • Ecological fallacy • Exception falalcy

  10. Ecological Fallacy • Occurs when you make conclusions about individuals based only on analyses of group data. • For instance, assume that you measured the math scores of a particular classroom and found that they had the highest average score in the district. Later (probably at the mall) you run into one of the kids from that class and you think to yourself, 'She must be a math whiz.' Aha! Fallacy! Just because she comes from the class with the highest average doesn't mean that she is automatically a high-scorer in math. She could be the lowest math scorer in a class that otherwise consists of math geniuses.

  11. Exception fallacy • Sort of the reverse of the ecological fallacy. • It occurs when you reach a group conclusion on the basis of exceptional cases. • The stereotype is of the guy who sees a woman make a driving error and concludes that women are terrible drivers. Wrong! Fallacy!

  12. Variables • Any entity that can take on different values • Characteristics of units that vary, taking on different values, categories, or attributes for different observations • May vary over cases, over time or over both cases and time • Example: • Age (range of years) • Gender (female & male) • Marital status (single, married, divorced, widowed, etc) • Level of education (primary, secondary, diploma, etc)

  13. Types of variables • Explanatory • Dependent variables • Independent variables • Antecedent variables • Intervening variables • Extraneous • Controlled • Uncontrollled • Qualitative & Quantitative

  14. Dependent-Independent • Dependent is variables that the researcher interested in explaining or describing • Independent is the explanatory variables that do the influencing and explaining, also called predictor variable • In terms of cause and effect, the independent variable is the presumed cause and the dependent variable is the presumed effect • For example: when the relationship between educational attainment (years of schooling) and income is studied, educational attainment is the IV and income is DV

  15. Antecedent variable occurs prior in time to both the independent and dependent variable Intervening variable occurs if it is an effect of the independent variable and a cause of the dependent variable Type of school (independent) Parent’s income (antecedent) Academic achievement (dependent) Type of school (independent) Amount of homework (intervening) Academic achievement (dependent) Antecedent & intervening

  16. Quantitative & Qualitative • A variable is quantitative if its value or categories consist of numbers and if differences between its categories can be expressed numerically • Income • Qualitative variables have discrete categories, usually designated by words or labels, and nonnumerical differences between categories • Gender  male & female

  17. RQ, Unit analysis and variables

  18. Relationship • Types of relationship: • Among Qualitative variables • Among Quantitative variables • Between Qualitative and Quantitative variables • Properties of relationship: • The extent of to which variables are associated or correlated • Strength • How changes in one variable are related to changes in another • Directionality • Linearity

  19. Relationship among qualitative variables

  20. Relationship among quantitative variables • Direction and linearity • Direction  positive vs negative • Linearity  linear vs curvilinear • A positive (direct relationship) between variables exists if an increase in the value of one variable is accompanied by an increase in the value of the other, or if a decrease in the value of one variable is accompanied by a decrease in the value of the other. • Sons’ heights and fathers’ heights (the taller the father, the taller the son will tend to be) • A negative (inverse relationship) between variables exists if a decrease in the value of one variable is accompanied by increase in the value of the other. • Speed and accuracy (the faster one does something, the less accuracy one is likely to do it)

  21. Relationship among quantitative variables (2)

  22. Relationship between qualitative and quantitative variables

More Related