This Workshop Still Available: Qualitative Research Methods August 11-22 10am-2pm School 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

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Quantitative Methods

for the Social and Behavioral Sciences Dr. Jamie Barden Department of Psychology [email protected]

Social and Behavioral Sciences

:study systematic processes of human behavior.

Level of Analysis  within 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 Operationalize Measure Evaluate Revise or Replicate

Hypothesis

: an explicit, testable prediction about the conditions under which an event will occur. Useful hypotheses should be 1. a priori: before data collection 2. 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 partner height, age attraction questionnaire Construct Validity: How well measures and manipulations reflect the variables they are intended to measure and manipulate.

Variables Conceptual (dictionary) Operational (concrete measures and manipulations) Example Fear

Pick One of Your Variables

Feeling scared or a behavioral tendency to distance the self from a stimuli 1. distancing behavior 2. questionnaire items 3. facial expression 4. skin conductance

Methodological Options: Social and Behavioral Sciences

Data Collection Approaches 1. Life Record Data 2. Field Study 3. Survey Research 4. Laboratory Research 5. Case Study 6. Focus Group 7. Modeling Types of Study A. Descriptive B. Correlational C. Experimental Which have you used?

Measure

Three 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. Observation 2. Historical records (archives) 3. Survey questionnaires Examples?

Descriptive Research Example

Gallup Daily Poll

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.

Population Sample

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).

Demos

 Name that method DEMO  Name that method for your research.

The End

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?

Measure: Experimental

 Advantage: can investigate quasi independent variables that are impossible or unethical to manipulate  Disadvantage: internal validity threats undermine causal conclusions