Documentary Analysis and Documentary Analysis and a Brief Introduction to Statsa Brief Introduction to Stats

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

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

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

  Positive Negative

Active Active Positive    

Active Negative

Passive Passive Positive    

Passive Negative

Typology Typology

ExamplesExamples

  Positive Negative

Active Active Positive JFKFDRJefferson   

Active NegativeNixonHooverJohnson

Passive Passive Positive Reagan   

Passive NegativeWashingtonEisenhower

MotivesMotives

  Positive Negative

Active Active Positive Rational Mastery   

Active NegativePower

Passive Passive Positive Affection   

Passive NegativeDuty

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

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

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

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

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

CohenCohen

Is unit of analysis appropriate?Is unit of analysis appropriate?

Are categories Appropriate?Are categories Appropriate?

Is SOTUA appropriate?Is SOTUA appropriate?

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

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

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

Measures of Central TendencyMeasures of Central Tendency

Mean (Average)Mean (Average)

MedianMedian

ModeMode

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

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

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

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

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

For Next TimeFor Next Time

Read chapter 11 on Univariate DataRead chapter 11 on Univariate Data