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Correlation


       Nabaz N. Jabbar
    Near East University
        25 Oct 2011
Definition of correlation

• Correlational research determines
  to what degree a relationship
  exists between 2 variables (or
  more variables).
The nature of correlational research
        • Associational research: When the
          relationships among two or more
          variables are studied without any
          attempt to influence them. (The
          same as correlation and causal
          comparative research).

        • Experimental research: Differs from
          correlational research in that
          there’s manipulation of variables.
The nature of correlational research
        • Correlational research is also
          sometimes referred to as a form of
          descriptive research because it
          describes an existing relationship
          between variables.
The nature of correlational research
        • Positive correlation means that
          high scores on one variable (X) tend
          to be associated with high scores
          on the other variable (Y).

        • Negative Correlation means that
          high scores on one variable (X) are
          associated with low scores on the
          other variable (Y).
Three Sets of Data Showing
Different Directions and Degrees of
            Correlation
        (A)                 (B)               (C)
     r = +1.00           r = -1.00           r=0

 X               Y   X               Y   X          Y
 5               5   5               1   2          1
 4               4   4               2   5          4
 3               3   3               3   3          3
 2               2   2               4   1          5
 1               1   1               5   4          2
A positive correlation



   y




                    x
A negative correlation



   y




                   x
No correlation



y




                 x
No correlation



y




                 x
Purposes of Correlational Research

• Correlational studies are carried out to
  explain important human behavior or to
  predict likely outcomes. (identify
  relationships among variables).

1. Explanatory studies
2. Prediction studies
3. More complex correlational techniques
Explanatory studies
 • To identify relationships among variables.
 Prediction studies
• If a relationship of sufficient magnitude exists
  between two variables, it becomes possible to
  predict score on one variable when score on
  related variable is known.
1. Predictor variable: The variable that is used
   to make the prediction.
2. Criterion variable: The variable about which
   the prediction is made.
Prediction Using a Scatterplot
More Complex Correlational
           Techniques
o Multiple Regression
o Coefficient of multiple correlation(R)
o Coefficient of Determination
o Discriminant Function Analysis
o Factor Analysis
o Path Analysis
o Structural Modeling
More Complex Correlational
           Techniques
• Multiple Regression
Technique that enables researchers to
  determine a correlation between a criterion
  variable and the best combination of two or
  more predictor variables.
• Coefficient of multiple correlation(R)
Indicates the strength of the correlation
  between the combination of the predictor
  variables and the criterion variable
More Complex Correlational
           Techniques
• Coefficient of Determination
Indicates the percentage of the variability
  among the criterion scores that can be
  attributed to differences in the scores on the
  predictor variable.
• Discriminant Function Analysis
Rather than using multiple regression, this
  technique is used when the criterion value is
  categorical.
More Complex Correlational
           Techniques
• Factor Analysis
 Allows the researcher to determine whether many
  variables can be described by a few factors.
• Path Analysis
 Used to test the likelihood of a causal connection
  among three or more variables.
• Structural Modeling
 Sophisticated method for exploring and possibly
  confirming causation among several variables.
Path Analysis Diagram
Correlation coefficient

• A decimal number between .00 and +1.00 or
  –1.00 that indicates the degree to which two
  quantitative variables are related.



        -1.00            0.00              +1.00


 strong negative                     strong positive
                   no relationship
Basic Steps in Correlational
                Research
   Problem selection
   Choosing a sample
   Selecting or choosing proper instruments
   Determining design and procedures
   Collecting and analyzing data
   Interpreting results
Threats to Internal Validity
        in Correlational Research
•   Subject characteristics
•   Mortality
•   Location                Instrument decay
•   Instrumentation         Data collector bias
•   Testing              Data collector characteristics

• The following must be controlled to reduce
  threats to internal validity
Partial Correlation

• A method of controlling
  the subject
  characteristics threat in
  correlational research
  by statistically holding
  one or more variables
  constant.
References
• Cohen, L., & Manion, L. (1985). Research methods
  in education. Sydney.
• Fraenkel, J., R., & Wallen, N., E., (1990). How to
  design and evaluate research in education. New
  York.
• http:// www. mcgraw-hill.com
• http://www. gandrewpage.com
• http://www. capilanou.ca

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Correlation

  • 1. Correlation Nabaz N. Jabbar Near East University 25 Oct 2011
  • 2. Definition of correlation • Correlational research determines to what degree a relationship exists between 2 variables (or more variables).
  • 3. The nature of correlational research • Associational research: When the relationships among two or more variables are studied without any attempt to influence them. (The same as correlation and causal comparative research). • Experimental research: Differs from correlational research in that there’s manipulation of variables.
  • 4. The nature of correlational research • Correlational research is also sometimes referred to as a form of descriptive research because it describes an existing relationship between variables.
  • 5. The nature of correlational research • Positive correlation means that high scores on one variable (X) tend to be associated with high scores on the other variable (Y). • Negative Correlation means that high scores on one variable (X) are associated with low scores on the other variable (Y).
  • 6. Three Sets of Data Showing Different Directions and Degrees of Correlation (A) (B) (C) r = +1.00 r = -1.00 r=0 X Y X Y X Y 5 5 5 1 2 1 4 4 4 2 5 4 3 3 3 3 3 3 2 2 2 4 1 5 1 1 1 5 4 2
  • 11. Purposes of Correlational Research • Correlational studies are carried out to explain important human behavior or to predict likely outcomes. (identify relationships among variables). 1. Explanatory studies 2. Prediction studies 3. More complex correlational techniques
  • 12. Explanatory studies • To identify relationships among variables. Prediction studies • If a relationship of sufficient magnitude exists between two variables, it becomes possible to predict score on one variable when score on related variable is known. 1. Predictor variable: The variable that is used to make the prediction. 2. Criterion variable: The variable about which the prediction is made.
  • 13. Prediction Using a Scatterplot
  • 14. More Complex Correlational Techniques o Multiple Regression o Coefficient of multiple correlation(R) o Coefficient of Determination o Discriminant Function Analysis o Factor Analysis o Path Analysis o Structural Modeling
  • 15. More Complex Correlational Techniques • Multiple Regression Technique that enables researchers to determine a correlation between a criterion variable and the best combination of two or more predictor variables. • Coefficient of multiple correlation(R) Indicates the strength of the correlation between the combination of the predictor variables and the criterion variable
  • 16. More Complex Correlational Techniques • Coefficient of Determination Indicates the percentage of the variability among the criterion scores that can be attributed to differences in the scores on the predictor variable. • Discriminant Function Analysis Rather than using multiple regression, this technique is used when the criterion value is categorical.
  • 17. More Complex Correlational Techniques • Factor Analysis  Allows the researcher to determine whether many variables can be described by a few factors. • Path Analysis  Used to test the likelihood of a causal connection among three or more variables. • Structural Modeling  Sophisticated method for exploring and possibly confirming causation among several variables.
  • 19. Correlation coefficient • A decimal number between .00 and +1.00 or –1.00 that indicates the degree to which two quantitative variables are related. -1.00 0.00 +1.00 strong negative strong positive no relationship
  • 20. Basic Steps in Correlational Research  Problem selection  Choosing a sample  Selecting or choosing proper instruments  Determining design and procedures  Collecting and analyzing data  Interpreting results
  • 21. Threats to Internal Validity in Correlational Research • Subject characteristics • Mortality • Location Instrument decay • Instrumentation Data collector bias • Testing Data collector characteristics • The following must be controlled to reduce threats to internal validity
  • 22. Partial Correlation • A method of controlling the subject characteristics threat in correlational research by statistically holding one or more variables constant.
  • 23. References • Cohen, L., & Manion, L. (1985). Research methods in education. Sydney. • Fraenkel, J., R., & Wallen, N., E., (1990). How to design and evaluate research in education. New York. • http:// www. mcgraw-hill.com • http://www. gandrewpage.com • http://www. capilanou.ca