intro to quantitative research

1. AN INTRODUCTION TO QUANTITATIVE RESEARCH
EDF 7486: Topic 1

2. Quantitative Research
What is quantitative research?
 Quantitative research collects and uses numerical data to
explore, describe, explain, or predict trends or phenomena.
 Quantitative research emphasizes objectivity and the control of
contextual factors that may impact the results.
 Quantitative research states hypotheses and relies on statistical
analysis to support conclusions made regarding the
hypotheses.

3. Reasons for Quantitative Research
Exploratory
 Investigates issues with the goal of providing insight and information to
the researcher
 Use pilot studies to test feasibility or value of working in an area; focus
groups to guide survey design
Description
 Describe the current situation or classify situations, events or groups.
 Often use large scale data sets -NELS, High School and Beyond, etc.
 Surveys; correlational studies

4. Reasons for Quantitative Research
Explanation
 Build, enrich and explain theories
 Test theories using quantitative methods
Prediction
 Establish predictors of some behavior
 Two types of variables – predictor and criterion (outcome)
 Regression analysis is one statistical procedure used for prediction
Evaluation
 Evaluates programs for their efficacy
 Come in different forms and serve different functions

5. Types of Quantitative Research
Survey Research
 Collect quantitative data to address questions about the
current state of a population or phenomena.
 Can address preferences, attitudes, opinions, concerns,
interests
Correlational Research
 Determines if a relationship exists between two quantitative
variables
 Measure the strength of the relationship

6. Types of Quantitative Research
Causal-Comparative Research
 Establish a cause, or reason, for a behavior or other
phenomena after the event, or cause, has already occurred.
 Involves an independent-dependent variable relationship.
Experimental Research
 A collection of research designs that uses one or more variables
that are manipulated to understand the effect on a dependent
variable.
 Allows for control of variables not relevant to the research.

7. Types of Quantitative Research
Action Research
 Conducted by school administrators, teachers, or any other
stakeholder in the teaching-learning environment
 Primary focus is on the way schools operate, teachers teach
and students learn

8. Four Parts of Quantitative Research
Measurement
Sampling
Research Design
Statistical Procedures

9. Properties of Measurement
Reliability
 Consistency
 Random error
Validity
 Interpretation/Use
 Most Important Property
 Systematic error
Reliability is necessary but not sufficient condition
for validity

10. Properties of Sampling
Population v Sample
Sampling Methods
 Probabilistic (e.g., random)
 Non-probabilistic (e.g., convenience)
Key is that sample is representative of population to
make a generalization in interpretation

11. Research Design
How to set up data collection to minimize counter
interpretations to the results
Control/Comparison Groups
Random Assignment

12. Random Selection vs. Random Assignment
Random selection--Each person of a population has
an equal chance of being included in the sample.
Random assignment--Each person of a sample has
an equal chance of being assigned to particular
group.

13. Statistical Procedures
Descriptive
 Describes sample data
Inferential
 Tests probability of sample data being drawn from population
defined by hypotheses

14. Criteria for Evaluating Social Research
Construct validity
 Refers to inferences made from measured variables to
theoretical constructs
 Examines how well assessment “matches up with” the
construct.
Internal validity
 Examines the extent to which the relationship between two
variables is isolated from the influences of additional variables.

15. Criteria for Evaluating Social Research
External validity
 Addresses the concern of how well does the relationship
between two variables generalize across settings, samples, and
times.
Statistical conclusion validity
 Addresses issue of how the use of statistics shape inferences
and interpretations