Topic 1 introduction to quantitative research

Topic 1 introduction to quantitative research

• 1.
  AN INTRODUCTION TOQUANTITATIVE RESEARCH EDF 7486: Topic 1
• 2.
  Quantitative Research What isquantitative 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 QuantitativeResearch 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 QuantitativeResearch 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 QuantitativeResearch 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 QuantitativeResearch 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 QuantitativeResearch 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 ofQuantitative 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 Populationv 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 toset 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  Describessample data Inferential  Tests probability of sample data being drawn from population defined by hypotheses
• 14.
  Criteria for EvaluatingSocial 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 EvaluatingSocial 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