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Compiling, evaluating, and presenting numerical evidence to support and illustrate arguments about politics and public affairs.  Numerical evidence:

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Presentation on theme: "Compiling, evaluating, and presenting numerical evidence to support and illustrate arguments about politics and public affairs.  Numerical evidence:"— Presentation transcript:

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3 Compiling, evaluating, and presenting numerical evidence to support and illustrate arguments about politics and public affairs.  Numerical evidence: social, political and economic indicators  Arguments: “informal” arguments consisting of one or more premise and a conclusions.

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5  A form of Inductive or Informal Argument Logical Fallacy:  When premises do not provide enough support for an argument’s conclusions.  Premises consist of time series, cross sectional and demographic numerical comparisons.  Note: Traditional hypothesis-testing research methods design defines a “deductive” argument structure, but only to establish a very limited conclusion.

6 A new national survey by the Pew Research Center finds that nearly one-in-five Americans (18%) now say Obama is a Muslim, CNN/Opinion Research Corporation survey, more than a quarter of the public have doubts about Obama's citizenship

7 More than half (51%) believe it is very likely or somewhat likely that government officials were "directly responsible for the assassination of President Kennedy.“ More than half (52%) believe it is likely that the CIA allowed drug dealers from Central America to sell crack cocaine to African- Americans in US inner cities.CIA

8 Nearly half (47%) believe it is very likely or somewhat likely that "The U.S. Air Force is withholding proof of the existence of intelligent life from other planets.”

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11  Data in text file Data in text file  Excel file: Excel file:  http://lilt.ilstu.edu/gmklass/pos138/cherry2.xlsx http://lilt.ilstu.edu/gmklass/pos138/cherry2.xlsx

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28  CPI adjustments for inflation overestimate inflation by %1 per year. Effect::  Underestimates of income and price growth  Overestimates of poverty rates  “Percentage of median family income,” minimizes price increases, most commonly:  University tuition and fees as a percentage of median family income.

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30  Treatment or Setting does not correspond to future policy  Hawthorne Effect  Multiple experimental treatments  Example: Third (rear window) brake light experiment  Example: Rats and cancer experiments

31  343 San Francisco taxicabs with CHMSL (Center High Mounted Stop Lamps)  160 taxis with no additional light (random assignment)  Findings: CHMSL taxis:: 61% fewer rear end crashes, 61% fewer driver injuries, 62% lower repair costs  On all cars since 1986  Later Finding: from 1989-95 CHMSLs reduced rear-end crashes by only 4.3%

32  History – something else happened at the same time to produce the effect  Maturation: long term processes affecting the results  Testing: the first test affects the scores on the second  Instrumentation: unreliable measures of effect All threats to internal validity are due to the lack of an equivalent or randomly assigned control group

33  Instability: another form of unreliable measures  Regression artifact: Policy was conducted on a group, a place, or at a time chosen for its high or low scores on the test. Example: Murder rates are higher in states with the death penalty All threats to internal validity are due to the lack of an equivalent or randomly assigned control group

34  Students who do the best on the first exam usually do worse on the second  Students who do the worst on the first exam usually do better on the second

35  Rudi Giuliani and New York City’s Crime Rate JPDA, pp 24-29  Election Day Registration JPDA, pp 91-95

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37 Issue: Why do 6 states with EDR average about 10% higher voter turnout Possible Reasons  Reverse causation: states where civic participation is valued are more likely to enact EDR  History:  Those states may have had very closely contested elections  Those states may have other policies that encourage turnout

38 Figure 4.7: State Voter Turnout* and Social Capital


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