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Human Inquiry and Science

Human Inquiry and Science. Holographic Overview. Questions for Discussion. What are the common errors of human inquiry? What are quantitative and qualitative data? What are independent and dependent variables? What is the relation of attributes?. Searching for answers.

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Human Inquiry and Science

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  1. Human Inquiry and Science Holographic Overview

  2. Questions for Discussion • What are the common errors of human inquiry? • What are quantitative and qualitative data? • What are independent and dependent variables? • What is the relation of attributes?

  3. Searching for answers • Human Inquiry: aimed at answering ‘what and why’ through observations and experiences • Tradition: accepting what everyone ‘knows’ • Authority: judgment of an expert

  4. Errors • Inaccurate Observations • Measurement devices • Overgeneralization • Large and representative samples • Replication: repeat and check • Possibly vary conditions • Selective Observation • Illogical Reasoning • Be careful with contradictions

  5. A Variable Language • Variable: a logical set of attributes • Attribute: characteristic Example Common Social Concepts See examples on page 15

  6. Dependent and Independent Variables • Use common sense and everyday language • Dependent variables are determined or caused by something; depends on something else • Independent variables have no dependence; they are what they are

  7. Idiographic and Nomothetic • Idiographic: seeks to explain a particular situation • Limited to the single case • Nomothetic: seeks to explain a class of situations • Generalizability

  8. Inductive versus Deductive • Inductive: from a set of specific observations to the discovery of a pattern that represents some degree of order among all the given events – particular to general • Deductive: from a pattern that might be logically or theoretically expected to observations that test whether the expected pattern actually occurs – general to specific

  9. Numerical versus Nonnumerical • Quantitative data are numerical • Qualitative data are nonnumerical • Both are useful for different purposes • Can be used in conjunction with one another

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