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NAEP-Howard Statistics and Evaluation Institute

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1 NAEP-Howard Statistics and Evaluation Institute
This Workshop Still Available: Qualitative Research Methods August am-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

2 Quantitative Methods for the Social and Behavioral Sciences
NAEP-Howard Statistics and Evaluation Institute NAEP-Howard Statistics and Evaluation Institute Quantitative Methods for the Social and Behavioral Sciences Dr. Jamie Barden Department of Psychology This means in this course we will not address qualitative methods such as ethnography, unstructured interviewing, textual analysis... Here we will focus on observations that can readily reduced to numerical form, and thus are subject to various empirical tests using statistics.

3 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 The focus of the current class is in the social and behavioral sciences. I am a psychologist, which means I am more used to focusing on the individual level of analysis and so in some ways what I present will perhaps be more focused on that level of analysis. There is of course the broader level of analysis at the social structure or societal level.

4 “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

5 -- Richard Feynman (1964) “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) Nobel prize winning physicist, involved in the development of the atomic bomb, understanding quantum mechanics. Truth in quotes because scientists always accept that truth is a temporary state that could change in the future, in the face of additional information.

6 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.

7 Hypothesis Operationalize Measure Evaluate Revise or Replicate

8 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

9 Hypothesis Where do hypotheses come from? Segue to Inspiration Has your hypothesis been explored already? Segue to Literature Review

10 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)

11 similar people will be more attracted to each other
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.

12 Example Fear Operational (concrete measures and manipulations) Conceptual (dictionary) Variables 1. distancing behavior 2. questionnaire items 3. facial expression 4. skin conductance Feeling scared or a behavioral tendency to distance the self from a stimuli Pick One of Your Variables

13 Methodological Options: Social and Behavioral Sciences
Data Collection Approaches Life Record Data Field Study Survey Research Laboratory Research Case Study Focus Group Modeling Types of Study Descriptive Correlational Experimental Which have you used? Life record data and field study do not allow for sufficient control for experimental designs, although field studies can use quasi-experimental designs.

14 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]

15 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?

16 Descriptive Research Example
Gallup Daily Poll

17 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. Sample Population A random sample (N=1000) allows us to generalize our findings back to THIS population. Estimate of Population (mean +/- %)

18 Measure: Descriptive Advantage: easy to do
Disadvantage: only involves 1 variable, so no information about relationships between variables.

19 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. What is the suggested direction of these effects? Which are continuous, which are categorical? Notice they can be either. Also, issues with measurement in each case. Finally third variable problems with last two.

20 Measure: Correlational
Advantage: study naturally occurring variables Disadvantage: correlation is not causation You cannot draw causal conclusions from correlational results.

21 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.

22 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? Which are IV and which are DV. Note, all IV’s have at least two discrete levels. You can design experiments that look at things you wouldn’t think.

23 Measure: Experimental
Advantage: cause/effect relationships Disadvantage: can’t manipulate all variables (impossible or ethical reasons).

24 Demos Name that method DEMO Name that method for your research.

25 The End

26 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 What other variables might we want to control? What are we randomly assigning to?

27 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.

28 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?

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

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