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220113P - LINEAR CORRELATION ANALYSIS

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Presentation at the Research Methodology Winter Camp AlMarefa University January 13, 2022 at 1.00pm. By Prof. Omar Hasan Kasule Sr. MB ChB (MUK). MPH (Harvard), DrPH (Harvard) Professor of Epidemiology and Bioethics, King Fahad Medical City

 

VARIABLES OF THE CLASSROOM DATA:

  • AGE (in years),
  • GENDER (male, female)
  • REGION of birth (East, North, West, Central, West),
  • ORDER in family (first, second, third, higher), D
  • DEGREE expected (bachelor, masters, doctorate, postdoctorate),
  • WEIGHT (in kilograms),
  • HEIGHT (in centimeters),
  • wearing GLASSES (yes, no),
  • COLOR preference (blue, red, green, yellow).

 

VARIABLES OF THE CLASSROOM DATA, Con’t.:

  • number of BROTHERS,
  • number of SISTERS,
  • type of primary SCHOOL (private, public),
  • type of UNIVERSITY (public, private), J
  • JUMPING rank (1st, 2nd, 3r etc.),
  • RUNNING rank (1st, 2nd, 3r etc.).

 

SPSS VARIABLE VIEW OF CLASSROOM DATA:



SPSS DATA VIEW OF CLASSROOM DATA:

 

DEFINITION OF CORRELATION:

  • Correlation analysis is used as preliminary data analysis before applying more sophisticated methods.
  • Correlation describes the relation between 2 random variables (bivariate relation like height and weight) about the same person or object with no prior evidence of inter-dependence.
  • Correlation indicates only association; the association is not necessarily causative.
  • Correlation measures linear relation and not variability.

 

FUNCTIONS OF CORRELATION:

  • Describing the relation between x and y.
  • Prediction of y if x is known.
  • Prediction of x if y is known.
  • Studying trends.
  • Studying the effect of a third factor on the relation between x and y.

 

FIGURE OF A SCATTERPLOT OF HEIGHT AND WEIGHT:



INTERPRETING THE CORRELATION COEFFICIENT:

  • 0.25 - 0.50 indicates a fair degree of association.
  • 0.50 - 0.75 indicates moderate to fair relation.
  • 0.75 indicate good to excellent relation.
  • r = 0 indicates either no correlation or that the two variables are related in a non-linear way.
  • Very high correlation coefficients may be due to collinearity.

 

FIGURES OF VARIOUS CORRELATION COEFFICIENTS:


FIGURES OF VARIOUS CORRELATION COEFFICIENTS: Con’t.- 1



FIGURES OF VARIOUS CORRELATION COEFFICIENTS: Con’t.- 2



FIGURES OF VARIOUS CORRELATION COEFFICIENTS: Con’t.- 3

 


 

FIGURES OF VARIOUS CORRELATION COEFFICIENTS: Con’t.- 4


 

FIGURES OF VARIOUS CORRELATION COEFFICIENTS: Con’t.- 5