Correlational research

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Correlational research

  1. 1. QUANTITATIVE RESEARCH METHODOLOGY Correlational Research
  2. 2. Correlational Research sometimes called "associational research" sometimes referred to as a form of descriptive research because it describes existing relationships between variable. illustrated graphically using scatterplot
  3. 3. What is a correlational research? investigates the possibility of relationships between variables there is no manipulation of variables describes the degree to which two or more quantitative variables are related and it does so by using a correlation coefficient
  4. 4. Purposes of Correlational Research To explain clarifies understanding of important phenomena by identifying relationships among the variables
  5. 5. Scatterplot showing a correlation of +1.00 Positive correlation means that high scores on one variable tend to be associated with high scores ont he other variable. While low scores on one are associated with low scores on the other.
  6. 6. Scatterplot showing a correlation of -1.00 Negative correlation means that high scores on one variable are associated with low scores on the other variable and low scores on one are associated with high scores on the other.
  7. 7. Scatterplot showing a 0 correlation
  8. 8. Purposes of Correlational Research To predict if a relationship of sufficient magnitude exists between two variables, it becomes possible to predict a score on one variable if a score in the other variable is known.
  9. 9. Prediction Studies Scatterplots for prediction construct a scatterplot calculate the regression line, which is the bais for prediction
  10. 10. Prediction Studies where Y'1 = the predicted score on Y (criterion variable) for individual (i) X1= individual i's sore on X (the predictor variable) a and b = values calculated mathematically from the orginal scores; constants for any given data. Y'1= a + bX1 Prediction equation express the regression line in the form of a prediction equation, which has the following form:
  11. 11. Other Correlational Techniques Multiple Regression enables researchers to determine a correlation between a criterion variable and the best combination of two or more predictor variables The coefficient of multiple correlation is symbolized by R. It indicates the strength of correlation between the comination of the predictor variables and the criterion variables.
  12. 12. Other Correlational Techniques The Coefficient of Multiple Correlation symbolized by R (multiple regression), which indicates the strength of correlation between the combination of the predictor variables and the criterion variables
  13. 13. Other Correlational Techniques The Coefficient of Determination the square of the correlation between a predictor and a criterion variable symbolized by r2 (simple regression) indicates the percentage of the variability among the criterion scores that can be attributed to differences in the scores on the predictor variable
  14. 14. Other Correlational Techniques The Discriminant Function Analysis Used when the criterion variable is categorical
  15. 15. Other Correlational Techniques The Factor Analysis determines whether many variables can be described by a few factors Path Analysis tests the likelihood of a casual connection among three or more variables
  16. 16. Steps in Correlational Research Problem Selection Sample Determination Identification of Instrument Form Design Data Collection Analysis and Interpretation

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