Educational Research: Correlational Studies

1. Educational Research: Correlational Studies EDU 8603 Educational Research Richard M. Jacobs, OSA, Ph.D.

2. Research... • The systematic application of a family of methods employed to provide trustworthy information about problems …an ongoing process based on many accumulated understandings and explanations that, when taken together lead to generalizations about problems and the development of theories

3. The basic steps of research... Scientific and disciplined inquiry is an orderly process, involving: recognition and identification of a topic to be studied (“problem”) description and execution of procedures to collection information (“method”) objective data analysis statement of findings (“results”)

4. Research methods... Quantitative… …collects and analyzes numerical data obtained from formal instruments

5. Quantitative methods... • descriptive research (“survey research”) • correlational research • causal-comparative research (“ex post facto research”) • experimental research

6. correlational research …determines whether and to what degree a relationship exists between two or more quantifiable variables …the degree of the relationship is expressed as a coefficient of correlation

7. …the presence of a correlation does not indicate a cause-effect relationship primarily because of the possibility of multiple confounding factors

8. A correlation study… …a study providing a numerical estimatethe correlation coefficientabout the relationship between two or more variables

9. Types of correlation studies… • relationship studies… …attempt to gain insight into variables that are related to more complex variables • prediction studies… …conducted to facilitate decisions about individuals, to aid in various types of selection, to test variables believed to be good predictors of a criterion, or to determine predictive validity of measuring instruments

10. Conducting a correlational study… 1. select the problem 2. select participants and instrument 3. design and procedure 4. data analysis and interpretation

11. 1. select the problem… …the variables to be correlated should be selected on the basis of some rationale …a shotgun or fishing approach is discouraged

12. 2. select participants and instrument… …using an acceptable sampling methodology, a minimum of 30 participants is acceptable …larger samples are used if validity and reliability are important because error measurement may mask the true relationship

13. 3. design and procedure… …two or more scores are obtained for each member of the sample, one score for each variable of interest, and the paired scores are then correlated …the result is expressed as a correlation coefficient

14. 4. data analysis and interpretation… …the two or more scores are obtained for each member of the sample, one score for each variable of interest, and the paired scores are then correlated …the correlation coefficient indicates the degree of relationship between the variables of interest

15. Correlation coefficient… -1.00 0.00 +1.00 strong positive strong negative no relationship

16. A positive correlation… y x

17. A negative correlation… y x

18. No correlation… y x

19. No correlation… y x

20. statistical significance… …a statement that the relationship between the variables, at a given level of probability (α, alpha), are truly related …is dependent upon the sample size

21. Conducting relationship studies… Follows the procedure for correlational studies with two adaptations… 1. data collection 2. data analysis and interpretation

22. relationship studies… …attempt to gain insight into variables that are related to complex variables …indicate whether causal-comparative and experimental studies may determine a causal connection between the variables

23. 1. select the problem… …the variables to be correlated should be selected on the basis of some rationale …identify an appropriate population of participants from which to sample …if needed, administer instrument to collect data

24. 2. data analysis and interpretation… …the scores for one variable are correlated with the scores for another variable and expressed in the form of a correlation coefficient

25. The method for computing a correlation coefficient… …depends upon the type of data represented by each variable …types of data: nominal (dichotomous) interval (continuous) ordinal (rank) ratio (continuous)

26. with continuous data… …use the product moment correlation, Pearson r (ρ, rho) • with rank data… …use the rank difference correlation, Spearman r (ρ, rho)

27. with dichotomous data… …use the phi correlation (ψ) • with curvilinear data… …use the eta correlation (η)

28. Conducting prediction studies… Follows the procedure for correlational studies with two adaptations… 1. data collection 2. data analysis and interpretation

29. predictive studies… …when two variables are highly related, scores on one variable can be used to predict scores on the other variable …facilitate decisions about individuals or to aid in various types of selection

30. predictor variable… …the variable used to predict criterion variable… …the variable predicted

31. 1. data collection… …valid measuring instruments should be carefully selected to represent the variables of interest …it is especially important that the measure used as the criterion variable be valid

32. 2. data analysis and interpretation… …single prediction studies use one predictor …multiple prediction studies use more than one predictor …in both, a continuous predictor variable is used to predict a continuous criterion variable

33. single prediction studies… Y = a + bX Where Y = predictor criterion X = an individual’s score on the predictor variable a = a constant calculated from the scores of all participants b = the coefficient indicating the contribution of the predictor to the criterion

34. multiple prediction studies… …use multiple predictors Y = a + bX1 + bX2 + … + bXn Where Y = predictor criterion Xn = an individual’s score on the predictor variable a = a constant calculated from the scores of all participants b = the coefficient indicating the contribution of the predictor to the criterion

35. discriminant function analysis …similar to multiple regression analysis but a continuous predictor variable is used to predict a categorical variable

36. path analysis …studies relationships and patterns among a number of variables, yielding a diagram showing the direct or indirect relationships between the variables

37. structural equation modeling …a sophisticated form of path analysis providing greater theoretical validity and statistical precision clarifying the direct or indirect interrelationships among variables relative to a given variable

38. canonical correlation …an extension of multiple regression analysis that produces a correlation based on a group of predictor variables and a group of criterion variables

39. factor analysis (FANOVA) …a statistical method for making sense of a large number of variables …approach: group a larger number of variables into a smaller number of clusters; derive factors by finding groups of variables that are highly among each other, but lowly with other variables; use factors as variables

40. Mini-Quiz… • True and false… …a high degree of correlation between two variables implies that one causes the other False

41. …the existence of a high negative correlation permits prediction True

42. …the correlation coefficient indicates the percentage of relationship between the variables False

43. …the correlation coefficient indicates the amount of common variance shared by the variables True

44. …common, or shared, variance indicates the extent to which variables vary in a systematic way True

45. …the more systematically two variables vary, the lower the correlation coefficient False

46. …the amount common, or shared, variance is much less than the numerical value of the correlation coefficient True

47. …for a given sample size, the value of the correlation coefficient needed for significance increases as the level of confidence increases True

48. …the level of significance indicates the probability that a given relationship is a true one, regardless of whether it is a strong or weak relationship True

49. …a statistically significant correlation coefficient establishes a cause-effect relationship False

50. …relationship studies that have not uncovered useful relationships have at least identified variables that can be excluded from future studies, which is a necessary step in science True