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Examining Relationships Between Variables

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Relationship between two quantitative variables measured on the SAME individuals ... Overall pattern. Striking deviations. Look at the scatterplot. Form: Linear ... – PowerPoint PPT presentation

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Title: Examining Relationships Between Variables


1
Examining Relationships Between Variables Part II
2
  • Relationship between two quantitative variables
    measured on the SAME individuals

3
  • Start
  • With
  • A
  • Scatterplot

4
  • IF Explanatory Response Relationship
  • then
  • Put explanatory variable on the x-axis
  • and
  • Put the response variable on the y-axis

5
  • Look at the scatterplot
  • Overall pattern
  • Striking deviations

6
  • Look at the scatterplot
  • Form Linear or non-Linear
  • Direction Positive or negative
  • Strength Strong, weak, moderately strong or
    weak
  • OUTLIERS?

7
  • IF roughly linear
  • Then
  • Calculate correlation coefficient, r
  • Which quantifies the direction and strength of
    the LINEAR relationship between the two variables.

8
Correlation Can we rely on our eye to judge the
strength of the relationship between two
variables?
9
Correlation Coefficient r Numerical measure of
the strength and direction of the relationship.
10
(No Transcript)
11
Average of the sum of the products of the
standardized variables using n-1 degrees of
freedom.
12
r is positive when the association is positive r
is negative when the association is
negative. WHY?
13
Negative
Positive
Negative x Negative Positive Positive x
Positive Positive Negative x Positive Negative
14
  • FACTS ABOUT CORRELATION
  • No distinction between x and y or explanatory and
    response variables.

15
  • Both variables must be quantitative.

16
r has no units. So r doesnt change if we
change the units of the variable.
17
  • -1 lt r lt 1
  • -1 means perfectly linear in negative direction.
  • 1 means perfectly linear in positive direction
  • 0 means no linear relationship

18
  • The relationship must be
  • LINEAR

19
  • r is not resistant to outliers

20
  • A study measured the physical strength of 200
    college men. One variable was the number of
    pull-ups a subject could do. Other variables
    included number of push-ups, number of sit-ups,
    and body weight. The correlations of pull-up
    count with these three variables were
  • r -0.150 r 0.190 r
    0.647
  • Which r goes with which variable?
  • www.whfreeman.com/tps3e

21
  • www.whfreeman.com/tps3e
  • 3.29
  • 3.31
  • 3.34
  • 3.36

22
  • The End
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