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NAEP-Howard Statistics and Evaluation Institute
This Workshop Still Available:
Qualitative Research Methods August 11-22 10am-2pmSchool of Education Bld. Room 216 Attendees will learn to apply various methods of qualitative inquiry, including ethnographic, structured and semi-structured interviewing, focus groups, document and content analysis, narrative inquiry, phenomenological studies, case study, observation, historical research, and action research.
Instructor: Dr. Dawn Williams, Chair of Department of Educational Administration and Policy.
You must apply separately for this workshop.
More information is available at www.HowardSEI.org.
NAEP-Howard Statistics and Evaluation Institute
Quantitative Methodsfor the Social and Behavioral Sciences
Dr. Jamie BardenDepartment of [email protected]
NAEP-Howard Statistics and Evaluation InstituteNAEP-Howard Statistics and Evaluation Institute
Social and Behavioral Sciences
:study systematic processes of human behavior.
Level of Analysiswithin individual: neuroscience, brain biology individual: psychology, behavioral genetics social structure: economics, anthropology,
sociology, political science, public health
“People like it when they understand something that they previously thought they couldn't understand. It's a sense of empowerment.”
--Neil DeGrasse Tyson, 2008
“What is the principal of science?
The test of all knowledge is experiment. Experiment is the sole judge of scientific 'truth'.”
“What business are you in as a scientist?
There is an expanding frontier of ignorance...”
-- Richard Feynman (1964)
Why use the scientific method?
To understand relationships between variables in our social world.
Empirically test predictions. (birds of a feather/opposites attract)
To allow others to independently verify findings.
Hypothesis: an explicit, testable prediction about the
conditions under which an event will occur.
Useful hypotheses should be 1. a priori: before data collection2. falsifiable: could be found false
Hypothesis
Where do hypotheses come from?
Segue to Inspiration
Has your hypothesis been explored already?
Segue to Literature Review
Operationalize
Conceptual variable: The general abstract definition of a variable. (like a dictionary definition)
Operational definition: The specific procedures for manipulating or measuring a conceptual variable. (concrete application)
Hypothesis (conceptual)
similar people will be more attracted to each other
Hypothesis (operational)
personality test choice of interaction partnerheight, age attraction questionnaire
Construct Validity: How well measures and manipulations reflect the variables they are intended to measure and manipulate.
1. distancing behavior
2. questionnaire items
3. facial expression
4. skin conductance
Example
Fear
Operational (concrete measures and manipulations)
Conceptual (dictionary)
Variables
Pick One of Your Variables
Feeling scared or a behavioral tendency to distance the self from a stimuli
Methodological Options: Social and Behavioral Sciences
Data Collection Approaches1. Life Record Data2. Field Study3. Survey Research4. Laboratory Research5. Case Study6. Focus Group7. Modeling
Types of StudyA. DescriptiveB. CorrelationalC. Experimental
Which have you used?
MeasureThree types of studies:
1. Descriptive: What is the level of 1 variable?
Ex: What is the president’s overall approval rating?
2. Correlational: How are 2 variables related?
Ex: How does survey respondent’s age relate to approval rating? [Predictor is measured]
3. Experimental: Does one variable cause the other?
Ex: Does dark vs. light skin in Barack Obama’s photos influence approval rating?
[The independent variable is manipulated]
Measure: Descriptive Descriptive Research: describes people using
the level of a single variable (a thought, feeling or behavior).
Types:1. Observation2. Historical records (archives)3. Survey questionnaires
Examples?
Population Sample
Measure: Descriptive Random Sampling: Selecting participants to be in
a study so that everyone in the population has an equal chance of being in the study.
A random sample (N=1000) allows us to generalize our findings back to THIS population.
Estimate of Population (mean +/- %)
Measure: Descriptive
Advantage: easy to do
Disadvantage: only involves 1 variable, so no information about relationships between variables.
Correlational Research: describes the relationship between two or more naturally occurring variables (predictor and criterion).
-Does having a resilient personality relate to mental health outcomes following natural disaster?
-Does pre-existing STD infection increase susceptibility to HIV infection?
-When the sun is out more, are people happier?
Which is the predictor variable? In correlational research the predictor is measured not manipulated.
Measure: Correlational
Advantage: study naturally occurring variables
Disadvantage: correlation is not causation
You cannot draw causal conclusions from correlational results.
Measure: Experimental Experimental Research: examines cause and
effect relationships between variables.
Independent Variable (IV) Variable that is the CAUSE of the dependent variable Variable that is manipulated by the experimenter
Dependent Variable (DV) Variable that is the EFFECT Variable that is measured
NOTE: The IV is manipulated, which helps make it independent of other variables.
Measure: Experimental
Examples (name the IV & DV): -Are children more likely to be aggressive after being shown violent media content to children (or is there no effect)?
-What impact does having a Black person (or not) in an otherwise White group have on decision making?
-Is someone more likely to be attracted to you if you emphasize your similarities or differences?
-How does alcohol consumption (or not) relate to male decision-making regarding sexual encounters?
Measure: Experimental
Advantage: cause/effect relationships
Disadvantage: can’t manipulate all variables (impossible or ethical reasons).
Measure: Experimental
random assignment—each participant in the experiment has to have an equal chance of being in any condition, so the conditions start the same. [DEMO]
25 participants needed per condition for a between-participants design.
½ are told about someone similar ½ told about someone different
Quasi-experiment
Lack of control over the assignment of participants to conditions and/or does not manipulate the causal variable of interest.
A quasi-independent variable is not a true independent variable that is manipulated by the researcher but rather is an event that occurred for other reasons.
Examples Does smoking cause cancer? Did 9/11 cause an increase in prejudice against
people of middle-eastern decent? Do Republican vs. Democratic presidents affect
the economy? Do extreme events (i.e., winning the lottery or
being paralyzed) affect day-to-day happiness? Does giving employees a raise or extra vacation
time boost productivity and job satisfaction? Does campus crime affect applicants to a
university?