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31 Cards in this Set
- Front
- Back
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Nonreactive Research |
Collecting data without participant awareness Can be Qualitative or Quantitative. |
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When should we do Nonreactive Research? |
-When data already exists -When there are concerns of reactivity -When there are no easy observations |
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What kind of data can be used? |
Don't re-invent the wheel! Get creative using data from banks, internet use, gov't database, other research, diaries, erosion. |
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How would you study Discrimination in a nonreactive manner?
Qualitative
Quantitiative |
? |
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How would you study Fast Food Consumption in a nonreactive manner?
Qualitative
Quantitiative |
? |
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How would you study Traffic Violations in a nonreactive manner?
Qualitative
Quantitiative |
? |
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How would you study Charity/ Volunteerism in a nonreactive manner?
Qualitative
Quantitiative |
? |
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What is Content Analysis? |
Taking words, symbols, messages that are communicated in text and turning it into numbers so they can be analyzed in a way that is objective and systematic
It can be qualitative or quantitative |
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What five steps should be taken when conducting Nonreactive Quantitative Content Analysis? |
1) Form research question 2) Pick a unit of analysis- what are you analyzing 3) Define the population 4) Define/ Operationalize variables 5) Analyze data/draw inferences |
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How might we code for frequency of Racism in FB statuses. |
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How might we code for direction of Racism in FB statuses. |
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How might we code for Intensity of Racism in FB statuses. |
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How might we code for space of Racism in FB statuses. |
? |
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What is the difference between Latent Coding and Manifest Coding and what are the pros and cons of each?
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Qualitative Latent- relies on subjective meaning based on interpretation, judgement and has fewer concrete rules. Pro's- context more natural "themes" human judgement
Quantitative Manifest-uses what we objectively see. Pros-reliable Cons-content loss |
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What needs to be considered when conducting Nonreactive Quantitative content analysis? |
Your research question, Unit of analysis, Sampling, Variables, Coding, Validity Causation, Ethics, Reliability, Appropriateness
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Name some Pros and Cons of Non-Reactive Quantitative Research |
Pros: Cheap, simple, looks to natural behaviour rather than a desirable response.
Cons- reliability concerns, difficult to infer causation, ethics about studying people and collecting data without their knowledge. |
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What is Deduction? |
When the Theory is present first and lead to seeking Data
Theory ---------> Data |
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What is Induction? |
When the Data is present and leads to the Theory
Data -----------> Theory
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What is Content Discourse |
Deals with reading about a topic over and over and recognizing patterns. |
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What is involved with Non reactive Quantitative Research? |
Coding: 1) Frequency: # of times 2)Direction: positive/negative tone 3) Intensity: magnitude (scale) 4) Space: % on a page
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Gorillas Poop Generously Every Day Among Massive Monkeys |
Goal- Traslate Process-"meaning" Generalization- limit/no replication Evidence-indirect/ incomplete Distortion- Interpretation Agency- "people have goals" Macro-Government Micro-Individual |
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What kinds of sources are involved with Nonreactive Qualitative
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Primary sources- horses mouth Secondary Sources- Summaries/ conclusions from other people. Other peoples data Running Records: Stats documents collected systematically over time Recollection: memory/oral history |
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Nonreactive Qualitative
What is involved in Nonreactive Qualitative Content Analysis? |
Content Analysis: -emphasizes latent content -identifying themes/links
1) Summarize- frequency/count data both latent and manifest 2) Conventional: Detect patterns/themes, develop theory, coding scheme from data. 3)Directional: use theory to develop coding scheme |
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What steps are involved with Quantitative Data Analysis?
Hint : There are 5 steps |
Step 1-Codebook- organization, what does 1 mean, 2, 3, 4 Step 2-Data Entry-spreadsheet Step 3- Data Cleaning- Check for mistakes in data entry. Step 4-Descriptive Stats look at data, interpret data, central tendency. Step 5- Inferential Stats- using stats to test hypothesis (t-test, f-test, Chi square, ANOVA Regression) Ho vs Ha
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What are the Pro's and cons of Step- 3 Data Cleaning? |
Pro's- Extreme data is non-representative, and can have disproportionately strong effects, it moves the line of your average.
Cons: Imperfect picture of real-world data, can be abused to bias or skew results |
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Descriptive statistics come in two flavours, what are they? |
Univariate and Multivariante |
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Describe Univariate Descriptive Stats |
Univariate Descriptive Stats: info on individual variables one variable at a time |
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Describe Multivarate Statistics? |
Multivariate à Information about relationship between two variables at once
Bivariate à Specifically about two variables |
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How would you visualize your data? |
We could use bar charts, histograms, pie charts |
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Describe Central Tendency and what is involved |
• Frequency gives us precise picture of the data • 3 measures of central tendency: • Mode: Most frequent value • Data can be unimodal, bimodal, multimodal • Mode: Sometimes we just want to know the most frequent response • Median: The value where ½ of the scores are beneath it • Organize scores, count to it • Median: Insensitive to extreme values, good for relative ranking
• Mean: Mathematical average
Sum of values / participants |
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What kinds of tests would you run for the following?
0 group 1 group 2 group 3 group |
IV # of Groups Test Continous 0 Reggression Discrete 1 One group t test Discrete 2 t test Discrete 3 ANOVA |
