Political Science 30 Political Inquiry

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Political Science 30Political Inquiry

1. Sections meet in Sequoyah Hall 142 this week,
   hold off on downloading SPSS
2. Midterm study guide now posted
3. Office hours 11-1pm today

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Variables and their Values

• You can think of any variable as a question
• What is the average lifespan in a country?
• The potential values that the variable can take
  on are possible answers to that question
• 45.9 years (Afghanistan)
• 71.1 years (The Bahamas)
• 50.2 years (Benin)
• 80.7 years (Japan)

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Values that independent variables take on for
different cases

• IV 1 Wealth. Per capita GDP takes on different
  values in different countries.
• Haiti 586
• Cuba 3267
• Spain 18,356
• USA 39,678

• IV 2 Health. Some countries have universal
  health care, some dont.
• Haiti, No
• Cuba, Yes
• Spain, Yes
• USA, No

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Measurement II. Quantifying and Describing
Variables

• Four Levels of Precision
• Measures of Central Tendency
• Mode
• Median
• Mean
• Measures of Dispersion
• Variance, Standard Deviation

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Four Levels of Precision For Measuring Variables
(Of Observations, p. 27)

• Nominal Measure You can put cases into a
  category, but cannot specify an order or
  relationship between the categories.
• Example The variable religion can take on
  values such as Catholic, Protestant, Mormon,
  Jewish, etc.

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Four Levels of Precision For Measuring Variables
(Of Observations, p. 28)

• Ordinal Measure You can put cases into different
  categories, and order the categories.
• Example The variable strength of religious
  belief can take on values such as devoutly
  religious, fairly religious, slightly religious,
  not religious.

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Four Levels of Precision For Measuring Variables
(Of Observations, p. 29)

• Interval Measure Not only can you order the
  categories of the variable, you can specify the
  difference between any two categories.
• Example. The variable temperature on the
  Fahrenheit scale can take on values such as 32
  degrees, 74 degrees, 116 degrees.

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Four Levels of Precision For Measuring Variables
(Of Observations, p. 30)

• Ratio Measure You can order categories, specify
  the difference between two categories, and the
  value of zero on the variable represents the
  absence of the variable.
• Example. The variable annual income can take
  on the values of 0, 98,000, or 694,294,129.

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Measures of Central Tendency(Of Observations,
Chapter 3)
Kobe Bryant 30,453,805 Nick Young 1,106,942
Pau Gasol 19,285,850 Jordan Farmar 1,106,942
Steve Nash 9,300,500 Shawne Williams 1,106,942
Steve Blake 4,000,000 Wesley Johnson 916,099
Jordan Hill 3,563,600 Xavier Henry 916,099
Chris Kaman 3,183,000 Robert Sacre 788,872
Jodie Meeks 1,550,000 Kendall Marshall 547,570
Ryan Kelly 490,180
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Measures of Central Tendency(Of Observations,
Chapter 3)

• Mode The most frequently occurring value.
• 1,106,942
• Median The midpoint of the distribution of
  cases.
• 1. Arrange cases in order
• 2. If the number of cases is odd, median is the
  value taken on by the case in the center of the
  list.
• 3. If the number of cases is even, median is the
  average of the two center values. 1,106,942

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Measures of Central Tendency(Of Observations, p.
60)

• Mean is the arithmetic average of the values that
  all the cases take on. 5,221,093
• Add up all the values
• Divide this sum by the number of cases, N.

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Measures of Dispersion(Of Observations, p. 94)

• The variance is a measure of how spread out cases
  are, calculated by
• Compute the distance from each case to the mean,
  then square that distance.
• Find the sum of these squared distances, then
  divide it by N-1. 73 trillion.

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Measures of Dispersion(Of Observations, p. 95)

• The standard deviation is the square root of the
  variance, 8,555,409.