1. Educational Research: Correlational Studies
Leonardo Veliz, 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. …is dependent upon the sample size
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

51. …the more correlation coefficients computed at one time, the more likely it is that some wrong conclusions about the existence of a relationship will be reached
True

52. …an appropriate population is one for which the data on each of the identified variables can be collected
True

53. …an artificial dichotomy is one where ordinal, interval, or ratio data are artificially turned into nominal data
True

54. …most correlational techniques assume that the relationship being investigated is linear
True

55. …a correction for unreliability should be used in prediction studies
False

56. …the greater the variability there is in each set of scores being correlated, the higher the correlation coefficient is likely to be
True

57. …in a prediction study, it is especially important that the measure used as the criterion be reliable
False

58. …one reason for shrinkage is that an initial predictor equation may be the result of chance relationship that will not be found again with another group of participants
True

59. correlation coefficient
…the mathematical expression of the degree of relationship between variables
correlation coefficient

60. shotgun or fishing approach
Fill in the blank…
…a research strategy in which the researcher correlates all sorts of variables to discover relationships
shotgun or fishing approach

61. statistical significance
…indicates that an obtained correlation coefficient is really different from a correlation of zero, or no relation, usually stated at a given level of probability
statistical significance

62. …a type of study in which a researcher identifies variables that are correlated with the dependent variable and removes their influence so that they will not be confused with that of the independent variable
relationship study

63. …a chart on which the variables to be correlated are placed which provides a visual representation of their relationship
scatter plot

64. …a relationship between variables in which an increase in one variable is associated with a corresponding increase in another variable up to a point, at which further increases in the first variable result in corresponding decreases in the other variable (or vice versa)
curvilinear

65. …the fact that correlation coefficients tend to be lowered if the measures being correlated have low reliability
attenuation

66. …the variable used to predict
predictor

67. …the variable that is predicted
criterion

68. …the tendency of a prediction equation to become less accurate when used with a group other than the one on which the equation was originally developed
shrinkage

69. …the procedure by which a prediction equation is validated with at least one other group and the variables no longer found to be related to the criterion measure are removed from the equation
cross-validation

70. multiple regression equation
…the equation used in a multiple prediction study
multiple regression equation

71. This module has focused on...
correlational studies
…which involve collecting data in order to determine whether, and to what degree, a relationship exists between two or more quantifiable variables

72. The next module will focus on...
causal-comparative studies
...which attempt to determine the cause, or reasons for pre-existing differences in groups of individuals