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A Short Guide to Action Research 4 th Edition. Andrew P. Johnson, Ph.D. Minnesota State University, Mankato www.OPDT-Johnson.com. Chapter 8: Quantitative Design in Action Research. Quantitative research is based on the collection and analysis of numerical data

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a short guide to action research 4 th edition

A Short Guide to Action Research4th Edition

Andrew P. Johnson, Ph.D.

Minnesota State University, Mankato

www.OPDT-Johnson.com

slide3

Quantitative research is based on the collection and analysis of numerical data

  • Three quantitative research designs can fit within the action research paradigm:

1. correlational research

2. causal–comparative research

3. quasi-experimental research

slide4

CORRELATIONAL RESEARCH

  • Seeks to determine whether and to what degree a statistical relationship exists between two or more variables
  • Used to describe an existing condition or something that has happened in the past
slide5

Correlation Coefficient

  • Correlation coefficient = the degree or strength of a particular correlation
  • Positive correlation = when one variable increases, the other one also increases
  • Negative correlation = when one variable increases, the other one decreases
  • Correlation coefficient of 1.00 = a perfect one-to-one positive correlation
  • Correlation coefficient of .0 = absolutely no correlation between two variables
  • Correlation coefficient of –1.00 = a perfect negative correlation
slide6
Misusing Correlational Research
  • Correlation does not indicate causation
  • Just because two variables are related, we cannot say that one causes the other

Negative Correlation

  • Increase in one variable causes a decrease in another
slide7
Making Predictions
  • Correlation coefficient identified by the symbol r
  • When r = 0 to .35, the relationship between the two variables is nonexistent or low
  • When r = .35 to .65, there is a slight relationship.
  • When r = .65 to .85, there is a strong relationship
slide8

CAUSAL-COMPARATIVE RESEARCH

  • Used to find reason for existing differences between two or more groups
  • Used when random assignment of participants for groups cannot be met
  • Like correlational research, used to describe an existing situation
  • compares groups to find a cause for differences in measures or scores
slide9

QUASI-EXPERIMENTAL RESEARCH

  • Like true experiment; but no random assignment of subjects to groups
  • random selection is not possiblein most schools and classrooms
  • Pre-tests and matching used to ensure comparison groups are relatively similar
slide10
Five Quasi-Experimental Designs
  • Exp = experimental group
  • Cnt = control group
  • O = observation or measure
  • T = treatment
slide16

THE FUNCTION OF STATISTICS

  • Descriptive statistics = statistical analyses used to describe an existing set of data
  • Measures of central tendency describes a set of data with a single number

a. mode - score that is attained most frequently

b. median - 50% of the scores are above and 50% are below

c. mean - the arithmetic average

slide17
Frequency Distribution = all the scores that were attained and how many people attained each score
slide19
Measures of variability = the spread of scores or how close the scores cluster around the mean

Range = the difference between the highest and lowest score

Variance = the amount of spread among the test scores

standard deviation = how tightly the scores are clustered around the mean in a set of data

slide20

Scores with a Small Variance

Scores with a Large Variance

slide24
INFERENTIAL STATISTICS
  • Inferential statistics = statistical analyses used to determine how likely a given outcome is for an entire population based on a sample size
  • make inferences to larger populations by collecting data on a small sample size
  • Statistical significance = that difference between groups was not caused by chance or sampling error