Documentary Analysis and a Brief Introduction to Stats.
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Transcript of Documentary Analysis and a Brief Introduction to Stats.
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Documentary Analysis and Documentary Analysis and a Brief Introduction to Statsa Brief Introduction to Stats
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Documentary AnalysisDocumentary Analysis
Allows access otherwise unobtainableAllows access otherwise unobtainable People you can’t interviewPeople you can’t interview Past EventsPast Events When speech is unit of analysisWhen speech is unit of analysis When behavior may be When behavior may be
unconscious/misreportedunconscious/misreported
Can be less expensiveCan be less expensive
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Types of SourcesTypes of Sources
Episodic RecordEpisodic Record Things in sporadic instancesThings in sporadic instances E.g. biographical information, things from a E.g. biographical information, things from a
specific time framespecific time frame
Running RecordRunning Record Repeated record in same wayRepeated record in same way E.g. Census, crime stats, state of union E.g. Census, crime stats, state of union
addressaddress
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Barber and the Episodic RecordBarber and the Episodic Record
Interested in how personality shapes Interested in how personality shapes presidential performancepresidential performanceLooks at biographical informationLooks at biographical information ChildhoodChildhood Early political ExperienceEarly political Experience MotivationsMotivations
Can’t interviewCan’t interviewNo running recordNo running recordNot particularly systematicNot particularly systematic
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Positive Negative
Active Active Positive
Active Negative
Passive Passive Positive
Passive Negative
Typology Typology
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ExamplesExamples
Positive Negative
Active Active Positive JFKFDRJefferson
Active NegativeNixonHooverJohnson
Passive Passive Positive Reagan
Passive NegativeWashingtonEisenhower
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MotivesMotives
Positive Negative
Active Active Positive Rational Mastery
Active NegativePower
Passive Passive Positive Affection
Passive NegativeDuty
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Origins of CharacterOrigins of CharacterFundamental orientationFundamental orientation
Childhood experienceChildhood experience
AP- Warmth and supportAP- Warmth and support
AN- DeprivationAN- Deprivation
Passives- Less clearPassives- Less clear
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Running RecordRunning Record
Anything that is available at multiple times in the Anything that is available at multiple times in the same waysame wayCensusCensusCrime reportsCrime reportsNews reportsNews reportsCongressional RecordCongressional RecordElection ReturnsElection ReturnsPolicyPolicyJudicial DecisionsJudicial Decisions
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Content AnalysisContent Analysis
Bridges Qualitative and Quantitative divideBridges Qualitative and Quantitative divide
Identify text/speech/content and turn into Identify text/speech/content and turn into numerical data in a systematic waynumerical data in a systematic way
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Content Analysis: How toContent Analysis: How to
Identify sample of materialsIdentify sample of materialsDefine Content CategoriesDefine Content CategoriesWhat is Recording Unit/Unit of Analysis What is Recording Unit/Unit of Analysis ArticleArticle SpeakerSpeaker SentenceSentence LineLine IdeaIdea
AnalyzeAnalyzeCheck Intercoder ReliabilityCheck Intercoder Reliability
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An Example: Presidential Agenda An Example: Presidential Agenda SettingSetting
Does presidential attention to issue make Does presidential attention to issue make it more important in the eyes of the public?it more important in the eyes of the public?
Looks at State of the Union AddressesLooks at State of the Union Addresses
Codes for Domestic, Foreign Policy, Civil Codes for Domestic, Foreign Policy, Civil Rights, Economic PoliciesRights, Economic Policies
Counts sentencesCounts sentences
Compares with changes (over time) in Compares with changes (over time) in public’s agenda public’s agenda
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CohenCohen
Is unit of analysis appropriate?Is unit of analysis appropriate?
Are categories Appropriate?Are categories Appropriate?
Is SOTUA appropriate?Is SOTUA appropriate?
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PercentagesPercentages
Useful for comparing groups with unequal Useful for comparing groups with unequal numbersnumbers
CABLE * APPROVE1 Crosstabulation
Count
92 39 90 149 370
308 123 335 596 1362
400 162 425 745 1732
.00
1.00
CABLE
Total
.00 .33 .67 1.00
APPROVE1
Total
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CABLE * APPROVE1 Crosstabulation
92 39 90 149 370
24.9% 10.5% 24.3% 40.3% 100.0%
5.3% 2.3% 5.2% 8.6% 21.4%
308 123 335 596 1362
22.6% 9.0% 24.6% 43.8% 100.0%
17.8% 7.1% 19.3% 34.4% 78.6%
400 162 425 745 1732
23.1% 9.4% 24.5% 43.0% 100.0%
23.1% 9.4% 24.5% 43.0% 100.0%
Count
% within CABLE
% of Total
Count
% within CABLE
% of Total
Count
% within CABLE
% of Total
.00
1.00
CABLE
Total
.00 .33 .67 1.00
APPROVE1
Total
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PercentagesPercentages
To Compute:To Compute: (#with trait of interest(#with trait of interest/t/total #) X 100otal #) X 100
Percentage of TotalPercentage of Total
Percentage of Valid CasesPercentage of Valid Cases Excludes missing casesExcludes missing cases Typically more appropriateTypically more appropriate
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Measures of Central TendencyMeasures of Central Tendency
Mean (Average)Mean (Average)
MedianMedian
ModeMode
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Computing the MeanComputing the Mean
Requires At least ordinal dataRequires At least ordinal data
(Y(Y11+ Y+ Y22+ Y+ Y33…. +Y…. +Yii)/I)/I
Example have people with incomes of Example have people with incomes of 10,000, 15,000, 25,000, 55,000, 32,000, 10,000, 15,000, 25,000, 55,000, 32,000, 29,50029,500
Mean=(10,000+15,000+25,000, +55,000+ Mean=(10,000+15,000+25,000, +55,000+ 32,000+29,500)/6= 27,75032,000+29,500)/6= 27,750
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Computing the MedianComputing the Median
Requires at least Ordinal DataRequires at least Ordinal Data
Put values in orderPut values in order
If odd number, value half are above, half belowIf odd number, value half are above, half below
If even number- Average of two middle casesIf even number- Average of two middle cases
Income Example:Income Example: 10,000, 15,000, 25,000, 55,000, 32,000, 29,50010,000, 15,000, 25,000, 55,000, 32,000, 29,500 10,000, 15,000, 25,000, 29,500, 32,000, 55,00010,000, 15,000, 25,000, 29,500, 32,000, 55,000 Median=25,250Median=25,250
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ModeMode
Most common with nominal dataMost common with nominal dataCount frequencies, find most commonCount frequencies, find most commonAsk 30 1Ask 30 1stst graders favorite color graders favorite color7 blue7 blue3 chartreuse 3 chartreuse 4 purple4 purple2 yellow2 yellow10 red10 red3 green3 green1 Black1 BlackMode- RedMode- Red
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When To Use Which?When To Use Which?
Mode- nominal dataMode- nominal data Better to actually give totals for all if few Better to actually give totals for all if few
choices, e.g. 33% red, 10% greenchoices, e.g. 33% red, 10% green
Mean- when appropriate dataMean- when appropriate data
Median- with ordinal data, in cases where Median- with ordinal data, in cases where there are a few values that might cause a there are a few values that might cause a skewskew
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Median vs. MeanMedian vs. Mean
Created a fake town with 100 residentsCreated a fake town with 100 residentsIncomes 190,00-138,000 Incomes 190,00-138,000 Mean=57600, Median=49,500Mean=57600, Median=49,500Suppose one person with 30,000 moves away, Suppose one person with 30,000 moves away, replaced by Millionairereplaced by Millionaire Mean=67,300, Median=55,000 Mean=67,300, Median=55,000
Replaced by 50,000,000Replaced by 50,000,000 Mean=557,300 Median= 55,000Mean=557,300 Median= 55,000
Replaced by Bill Gates (50 BillionReplaced by Bill Gates (50 Billion Mean=500Million, Median= 55,000Mean=500Million, Median= 55,000
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For Next TimeFor Next Time
Read chapter 11 on Univariate DataRead chapter 11 on Univariate Data