CHAP 11

• association between scores

  on two variables.

  correlation
• graph showing the relationship between two variables: the values of one variable are along the

  horizontal axis and the values of the

  other variable are along the vertical

  axis; each score is shown as a dot in

  this two-dimensional space.

  scatter diagram
• relation between

  two variables that shows up on a scatter

  diagram as the dots roughly following a

  straight line.

  linear correlation
• relation between two variables that shows

  up on a scatter diagram as dots following

  a systematic pattern that is not a

  straight line.

  curvilinear correlation
• no systematic relationship between two variables.

  no correlation
• relation between two variables in which high scores on one go with high scores on the other,

  mediums with mediums, and lows with

  lows; on a scatter diagram, the dots

  roughly follow a straight line sloping up

  and to the right.

  positive correlation
• relation between two variables in which high scores on one go with low scores on the other,

  mediums with mediums, and lows with

  highs; on a scatter diagram, the dots

  roughly follow a straight line sloping

  down and to the right.

  negative correlation
• the result of multiplying a person’s Z score on

  one variable by the person’s Z score

  on another variable.

  cross-product of Z scores
• The result of dividing the sum of the products of Z scores by the number of people in

  the study is called the

  correlation coefficient (r)
• who credited with inventing the correlation statistic.


  Sir Francis Galton
• path of causal effect; if X is thought to cause Y then the direction of causality is from X to Y.

  direction of causality
• any research design other than a true

  experiment.

  correlational research design
• worked out the formulas in correlation


  Karl Pearson