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Inductive Reasoning

Basic Categories. . Basic Categories. Target - the category we are interested in understanding better. Basic Categories. Target - the category we are interested in understanding betterSample - the individual or group we already know about or understand. Basic Categories. Target - the category we

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Inductive Reasoning

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    1. Inductive Reasoning Concepts and Principles of Construction

    2. Basic Categories

    3. Basic Categories Target - the category we are interested in understanding better

    4. Basic Categories Target - the category we are interested in understanding better Sample - the individual or group we already know about or understand

    5. Basic Categories Target - the category we are interested in understanding better Sample - the individual or group we already know about or understand

    6. Basic Categories Target - the category we are interested in understanding better Sample - the individual or group we already know about or understand

    7. Basic Categories Target - the category we are interested in understanding better Sample - the individual or group we already know about or understand

    8. Basic Categories Target - the category we are interested in understanding better Sample - the individual or group we already know about or understand

    9. Basic Categories Target - the category we are interested in understanding better Sample - the individual or group we already know about or understand Feature in question - the property we know about in the sample and wonder about in the target

    10. Using the basic categories... Will the governor cut funding for the CSU? Target - the governor’s budget agenda (needs to be an identifiable thing)

    11. Using the basic categories... Will the governor cut funding for the CSU? Target - the governor’s budget agenda (needs to be an identifiable thing) Sample - whatever we already know about his support for education

    12. Using the basic categories... Will the governor cut funding for the CSU? Target - the governor’s budget agenda (needs to be an identifiable thing) Sample - whatever we already know about his support for education Feature in question - funding for education (notice that the sample's features may not correspond perfectly to those of the target)

    13. Two Main Types of Inductive Reasoning Inductive generalization - intends a conclusion about a class of things or events larger than the subset that serves as the basis for the induction

    14. Two Main Types of Inductive Reasoning Inductive generalization - intends a conclusion about a class of things or events larger than the subset that serves as the basis for the induction

    15. Two Main Types of Inductive Reasoning Inductive generalization - intends a conclusion about a class of things or events larger than the subset that serves as the basis for the induction Analogical argument - intends a conclusion about a specific thing, event, or class that is relevantly similar to the sample

    16. Concerns About Samples Is the sample representative?

    17. Concerns About Samples Is the sample representative?

    18. Concerns About Samples Is the sample representative?

    19. Concerns About Samples Is the sample representative?

    20. Concerns About Samples Is the sample large enough?

    21. Concerns About Samples Is the sample large enough?

    22. Concerns About Samples Is the sample large enough?

    23. Focus Point: Fallacy of Anecdotal Evidence

    24. Focus Point: Fallacy of Anecdotal Evidence The sample is small, typically a single story

    25. Focus Point: Fallacy of Anecdotal Evidence The sample is small, typically a single story The story may be striking

    26. Focus Point: Fallacy of Anecdotal Evidence The sample is small, typically a single story The story may be striking The story is treated as though it were representative of the target

    27. Focus Point: Fallacy of Anecdotal Evidence The sample is small, typically a single story The story may be striking The story is treated as though it were representative of the target Best use of the anecdote: to focus attention (NOT as key premise)

    28. Confidence and Caution

    29. Confidence and Caution As sample size grows: either confidence increases or margin of error decreases

    30. Confidence and Caution As sample size grows: either confidence increases or margin of error decreases Inductions never attain 100% confidence or 0% margin of error

    31. Confidence and Caution As sample size grows: either confidence increases or margin of error decreases Inductions never attain 100% confidence or 0% margin of error In many cases, evaluation of these factors can be reasonable without being mathematically precise

    32. Mathematical Note: Law of Large Numbers

    33. Analogical Reasoning: The Argument from Design

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