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Lecture 6 - Student201205 ecs

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    1

    FHHM 1012 Critical Thinking

    Lecture 6

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    2

    TOPIC 5

    (INDUCTIVE REASONING 1)

    i) Inductionii) Analogy

    iii) Numbers

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    Lecture Notes 2008 McGraw HillHigher Education 3

    Inductive Argument

    Inductive Argument: an argument in whichthe premises are intended to provide support, butnot conclusive evidence, for the conclusion.

    Strong Inductive Argument: an inductiveargument in which the premises actually do makethe conclusion more likely to be true (rather thanfalse).

    Remember, strength comes in degrees.

    Cogent Inductive Argument: a stronginductive argument with true premises.

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    How can you know if the argument isinductive?

    If the arguments conclusiondoes notfollow with strict logical necessity fromits premises, the argument shouldnormally be treated as inductive.

    Indicator words: likely, probably, its plausible(possible/probable/believable/ reasonable) tosuppose that, etc.

    Common patterns: Analogy, Statistical,Causal and Generalization

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    INDUCTIVE ARGUMENT

    An inductive argument is one inwhich the premises are supposed tosupport the conclusion in such away that if the premises are true, itis improbable that the conclusionwould be false. Thus, the conclusion

    follows probably from the premisesand inferences.

    Lecture Notes 2008 McGraw HillHigher Education 5

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    INDUCTIVE ARGUMENT

    Example of an inductive argument:

    1. Socrates was Greek. (premise)

    2. Most Greeks eat fish. (premise)3. Socrates probably ate fish.(conclusion)

    Note: Premises do not provide

    conclusive (convincing/ certain)evidence for the conclusion.

    Lecture Notes 2008 McGraw HillHigher Education 6

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    STRONG INDUCTIVEARGUMENT

    A strong induction is an argumentin which the truth of the premiseswould make the conclusion probable

    but not require it as being factual.

    All observed crows are black.

    Therefore: All crows are black.

    Lecture Notes 2008 McGraw HillHigher Education 7

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    STRONG INDUCTIVE

    ARGUMENT

    The sample of crows was unbiasedand large enough.

    Thousands of randomly observedcrows over hundreds of years areblack.

    We have good reason to accept the

    conclusion as probably true, so theargument is strong.

    Lecture Notes 2008 McGraw HillHigher Education 8

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    Lecture Notes 2008 McGraw HillHigher Education 9

    Argument by Analogy Comparison of things based on similarities.

    Argument from analogy: an argument thatsuggests that the presence of certain

    similarities is evidence for further similarities.

    Common Form:1. A has characteristic X2. B has characteristic Y

    3. A has characteristic Y4. So B probably has characteristic Y too.

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    Argument by Analogy Example:

    1. Tiffany and Heather are both tall andplay basketball.

    2. Tiffany also plays volleyball.

    3. So, Heather probably plays volleyballtoo.

    Lecture Notes 2008 McGraw HillHigher Education 10

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    Lecture Notes 2008 McGraw HillHigher Education 11

    Evaluating Arguments from Analogy

    Are the premises true?

    Are the similarities relevant? Since being tall is helpful in volleyball,

    the fact that both Tiffany and Heatherare tall is relevant to the previousconclusion.

    The more relevant similaritiesthere are, the better. If we also learn that they both get

    scholarships if they play more than onesport, our conclusion is more supported.

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    Are there relevant dis-similarities?

    Irrelevant dis-similarities: hair color

    Relevant dis-similarity: job status

    The more examples which are alsosimilar, the better.

    If Amber and Krissy are also tall and play both

    basketball and volleyball our conclusion is evenfurther supported.

    Evaluating Arguments from Analogycont.

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    The more diversity in theexamples, the better. If Tiffany, Amber and Krissy are different in many

    ways, except for the fact that they are all tall andplay basketball and volleyball, it seems morelikely that their being tall and playing basketballis relevant to their playing volleyball. Thus,Heathers being tall and playing basketball isbetter evidence that she also plays volleyball.

    Is the conclusion too specific?Heather probably plays volleyball is better

    supported than Heather must play volleyball.

    Evaluating Arguments from Analogy cont.

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    Lecture Notes 2008 McGraw HillHigher Education 14

    Arguing by Analogy

    Employ the same questions andevaluation as you construct your ownarguments from analogy.

    Dont be too specific.

    Use relevant similarities.

    Use many similarities.

    Use a diverse and large group.

    Use true premises.

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    Pupils are more like oysters thansausages. The job of teaching is not tostuff them and then seal them up, butto help them open and reveal the richeswithin. There are pearls in each of us, ifonly we knew how to cultivate them

    with ardor(love/passion/enthusiasm)and pers is tence(determinat ion) .

    (Sydney J. Harris, "What True Education Should Do," 1964)

    Exercise: Identify the Analogy

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    Numbers

    Numbers are a way of measuringand also important in reasoning.

    Numbers can be misleading or usedwrongly.

    A vague claim doesnt get anybetter by using numbers.

    Lecture Notes 2008 McGraw HillHigher Education 16

    http://images.google.com.my/imgres?imgurl=http://thumb18.shutterstock.com.edgesuite.net/display_pic_with_logo/284044/284044,1229715705,1/stock-photo-close-up-of-stock-market-numbers-and-graphs-hit-by-bulls-eye-22262221.jpg&imgrefurl=http://www.shutterstock.com/pic-22262221/stock-photo-close-up-of-stock-market-numbers-and-graphs-hit-by-bulls-eye.html&usg=__sCuiDXOufn3kanytLRrCbNUiRPc=&h=470&w=300&sz=56&hl=en&start=6&um=1&tbnid=88bP2N9MgFpiGM:&tbnh=129&tbnw=82&prev=/images?q=Numbers+and+graphs&hl=en&sa=N&um=1http://images.google.com.my/imgres?imgurl=http://thumb18.shutterstock.com.edgesuite.net/display_pic_with_logo/284044/284044,1229715705,1/stock-photo-close-up-of-stock-market-numbers-and-graphs-hit-by-bulls-eye-22262221.jpg&imgrefurl=http://www.shutterstock.com/pic-22262221/stock-photo-close-up-of-stock-market-numbers-and-graphs-hit-by-bulls-eye.html&usg=__sCuiDXOufn3kanytLRrCbNUiRPc=&h=470&w=300&sz=56&hl=en&start=6&um=1&tbnid=88bP2N9MgFpiGM:&tbnh=129&tbnw=82&prev=/images?q=Numbers+and+graphs&hl=en&sa=N&um=1
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    Misleading claims with numbers

    Example (i): Zoe has 4 apples andZack has 2 oranges. Who has more?

    More of what? A vague (unclear)or meaningless

    comparison gets no better byhaving a few numbers in it.

    Lecture Notes 2008 McGraw HillHigher Education 17

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    Misleading claims with numbers

    Example (ii) : There were twice asmany rapes as murders in our town

    Lecture Notes 2008 McGraw HillHigher Education 18

    Yes, thats a claim , but a misleading one.

    It seems to say something important, butwhat?

    Is this a claim?

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    Misleading claims with numbers

    Example (iii):

    There were nearly 7.2 millionpeople around the globe in year

    2000 who had at least $1 million ininvestable assets.

    Lecture Notes 2008 McGraw HillHigher Education 19

    What is the source of the figures?

    What study?Who wants to let people know that theyre rich?

    Therefore, this is a worthless report.

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    Graphs

    Useful in making comparisonsclearer.

    Have to be careful wheninterpreting graphs because theycan conceal claims, mislead and justbe wrong.

    Lecture Notes 2008 McGraw HillHigher Education 20

    http://images.google.com.my/imgres?imgurl=http://www.eecis.udel.edu/~ntp/ntpfaq/loopstat.png&imgrefurl=http://www.eecis.udel.edu/~ntp/ntpfaq/NTP-s-trouble.htm&usg=__ATfpVskJ-jvusie446tDfzXRyNs=&h=480&w=640&sz=12&hl=en&start=41&um=1&tbnid=CbnNTGBoqHUN6M:&tbnh=103&tbnw=137&prev=/images?q=Numbers+and+graphs&ndsp=20&hl=en&sa=N&start=40&um=1http://images.google.com.my/imgres?imgurl=http://www.eecis.udel.edu/~ntp/ntpfaq/loopstat.png&imgrefurl=http://www.eecis.udel.edu/~ntp/ntpfaq/NTP-s-trouble.htm&usg=__ATfpVskJ-jvusie446tDfzXRyNs=&h=480&w=640&sz=12&hl=en&start=41&um=1&tbnid=CbnNTGBoqHUN6M:&tbnh=103&tbnw=137&prev=/images?q=Numbers+and+graphs&ndsp=20&hl=en&sa=N&start=40&um=1http://images.google.com.my/imgres?imgurl=http://www.eecis.udel.edu/~ntp/ntpfaq/loopstat.png&imgrefurl=http://www.eecis.udel.edu/~ntp/ntpfaq/NTP-s-trouble.htm&usg=__ATfpVskJ-jvusie446tDfzXRyNs=&h=480&w=640&sz=12&hl=en&start=41&um=1&tbnid=CbnNTGBoqHUN6M:&tbnh=103&tbnw=137&prev=/images?q=Numbers+and+graphs&ndsp=20&hl=en&sa=N&start=40&um=1
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    Graphs

    Lecture Notes 2008 McGraw HillHigher Education 21

    Why do the graphs look different?

    The vertical scales differ ( Misleading)

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    Graphs

    Explain why the graphs look different.

    The graphs look different due to the differentvertical scales. Graph A appears to show a more

    rapid decrease in sales than graph B.

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    Averages

    Example:

    It ought to be safe to cross here. I

    heard that the average depth is onlytwo feet.

    Beware: The average is not themaximum or most likely depth.

    Lecture Notes 2008 McGraw HillHigher Education 23

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    Averages

    The average or mean : collection ofnumbers is obtained by adding thenumbers and then dividing by thenumber of items.

    Example: The average of1,2,3,4,5,5 ,8 is calculated:

    Add: 1+2+3+4+5+5+8= 28

    Divide: 28 by 7= 4 (The average)

    Lecture Notes 2008 McGraw HillHigher Education 24

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    Averages

    Median : The midway mark, thesame number of items above andbelow.

    Example median of 1,2,3,4,5,5,8 is 4

    Mode : The number most oftenobtained.

    Mode for 1,2,3,4,5,5,8 is 5

    Lecture Notes 2008 McGraw HillHigher Education 25

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    Averages

    Unless the average is pretty close tothe median, the average does nottell you anything important.

    Lecture Notes 2008 McGraw HillHigher Education 26

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    Identifying Variables

    o VariableAny observation that cantake different values.

    o Examples:

    o Raceo gender

    o curriculum used

    o student outcomes

    o

    math programo student attitude

    o parent satisfaction

    Lecture Notes 2008 McGraw HillHigher Education 27

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    Two Kinds of Variables

    Independent variable (IV) variable that is varied or manipulated by the researcher

    Dependent variable (DV) the response that is measured

    Choice of IV Change in the DV(actions/interventions) ( results/outcomes)

    Lecture Notes 2008 McGraw HillHigher Education 28

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    Some tips!

    In the statement a researcher is measuring

    the effect of chocolate on happiness

    Start by identifying the dependent variable.

    What is actually being measured in theexperiment?

    DV: happiness

    happiness is affected by chocolate, or

    happiness depends on chocolate.

    www.sci.sdsu.edu 29

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    Identify the independent variable.

    If a researcher is measuring the effect of

    chocolate on happiness, the IV is chocolate.

    This is the variable that the experimenter

    will manipulate to see how it affects the

    dependent variable (in this case

    happiness).

    www.sci.sdsu.edu 30

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    Example 1

    "There will be a statistically significant difference in

    graduation rates of at-risk high-school seniors who

    participate in an intensive study program as opposed to

    at-risk high-school seniors who do not participate in the

    intensive study program."

    (LaFountain & Bartos, 2002, p. 57)

    IV :

    DV :

    http://www.uncp.edu 31

    http://www.uncp.edu/http://www.uncp.edu/
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    Example 2

    32

    A researcher is studying the effect of sleep on

    aggression, thinking that less sleep will lead to more

    aggression. She has some people sleep 6 hours per

    night, some people sleep 3 hours per night and some

    people sleep as much as they want. She thenmonitors aggressive behavior during basketball

    games among participants.

    IV :

    DV :

    http://www.sci.sdsu.edu

    http://www.sci.sdsu.edu/http://www.sci.sdsu.edu/
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    Example 3

    A researcher is curious to find out what effect classical

    music has on peoples level of relaxation (as measured

    by heart rate). He suspects that listening to classical

    music will make people feel more calm and relaxed.

    He lets one group listen to classical music for onehour. He lets another group sit in a quiet room for one

    hour (i.e they hear no music). After one hour, he

    monitors the heart rate of each participant to measure

    their level of relaxation.

    IV :

    DV :

    33http://www.sci.sdsu.edu

    http://www.sci.sdsu.edu/http://www.sci.sdsu.edu/
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    Reference:

    Epstein, RL. (2006). Critical Thinking. (3rd

    ed.) Belmont: Wadsworth.(pg 253 275)

    Basham, G., Irwin, W., Nardone, H. &

    Wallace, JM. (2008). Critical Thinking: A

    Students Introduction. (3rd ed.) New York:

    McGraw-Hill.(pg 312 - 321)

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    Overview of Todays Lecture

    Common Patterns of InductiveReasoning

    Induction

    Argument from Analogy

    Statistical Argument

    Questions or Enquiries???

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    The End


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