Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Correlation coefficient

  • Login to see the comments

Correlation coefficient

  1. 1. Correlation Coefficient ELESTA1
  2. 2. Correlation <ul><li>Measure of relationship between two variables </li></ul><ul><li>Ex. Grades in English tends to be related with Foreign Language </li></ul><ul><li>Height and weight </li></ul>
  3. 3. Nature of Correlation <ul><li>Magnitude/direction of the relationship </li></ul><ul><li>Strength of the relationship </li></ul><ul><li>Variance explained </li></ul><ul><li>Significance of the relationship </li></ul>
  4. 4. Magnitude of the Relationship <ul><li>Positive relationship – as one variable increases the other variable also increases </li></ul><ul><li>Ex. academic grades and intelligence </li></ul><ul><li>Negative relationship – as one variable increases, the other decreases or vice versa </li></ul><ul><li>Ex. procrastination and motivation </li></ul><ul><li>Absence of relationship between variables – denoted by .00 </li></ul>
  5. 5. Strength of Relationship <ul><li>A correlation coefficient is computed for a bivariate distribution using a statistical formula </li></ul>Correlation Coefficient Value Interpretation 0.80 – 1.00 Very strong relationship 0.6 – 0.79 Strong relationship 0.40 – 0.59 Substantial/marked relationship 0.2 – 0.39 Low relationship 0.00 – 0.19 Negligible relationship
  6. 6. Variance <ul><li>How much of Y’s is explained/accounted for by X </li></ul><ul><li>Proportion explained </li></ul><ul><li>Square of the correlation coefficient value </li></ul>
  7. 7. Conditions in interpreting r <ul><li>Linear regression – the points in a scatterplot should tend to fall along a straight line </li></ul><ul><li>The size of the r reflects the amount of variance that can be accounted for by a straight line </li></ul><ul><li>Homosedasticity – tendency of the standard deviation (or variances) of the arrays to be equal. </li></ul>
  8. 8. Correlational Techniques <ul><li>Pearson Product-Moment correlation – (r) used for interval/ratio sets of variables </li></ul><ul><li>Spearman Rank-order correlation – two sets of data are ordinal </li></ul><ul><li>Phi coefficient – each of the variables is a dichotomy </li></ul>

×