correlation – pmcc monday 18 th march 2013 learning objective: to be confident finding the product...
TRANSCRIPT
Correlation – PMCC
Monday 18th March 2013
Learning objective:To be confident finding the Product Moment Correlation Coefficient and using it to interpret data.
• Accuracy
• Interpretation
Starter: Can you find my mistakes?
Product moment correlation coefficient
Weight, x Calories, y x2 y2 xy
A 85 250
B 74 222
C 57 185
D 62 190
E 81 239
6th
6th
n
yxxySxy
nx
xSxx
2
2 )(
ny
ySyy
2
2 )(
(∑x)2 (∑y)2 ∑x∑y
7th
7th
yyxx
xy
SS
Sr
∑x = ∑y2 = ∑x2 = ∑y = ∑xy =
( When two sets of random variables bivariate) ; data are displayed on a scatter graph we
are used to describing the correlation but how
?do you measure it
( ) Two sets of random variables bivariate data we can describe correlation but how do you
?measure it x - = -y - = +- x + = -
x - = +
y - = +
+ x + = +
x
x
y
x - = -
y - = -
- x - = +
yx
xy
x - = +y - = - + x - = -yx
– ?Covariance how do you interpret it
When the covariance is positive it suggests positive correlation
When covariance is negative it suggests negative correlation
When the covariance is close to zero .it suggests no correlation
covariance
xySn
yyxx
– Covariance can you see any potential ?problems with this method alone
– When the covariance is positive it suggest positive correlation
– When covariance is negative it suggest negativecorrelation
– When the covariance is close to zero it suggests no.correlation
:You guessed it– ( ’ )you don t know the range
covariance
xySn
yyxx
Pearson Moment Correlation Coefficient
Karl Pearson
1857 - 1936
Is to standardise the covariance so that it can interpreted easily. It converts the covariance to a number between -1 to 1, where:
• -1 is a perfect negative correlation
• 1 is a perfect positive correlation
• 0 is no correlation
2 2
x x y y
nrx x y y
n n
The effect of scaling
If you work out the correlation coefficient for
- & ( ) sales of ice cream temperature t in
. Fahrenheit Would you expect the correlation to
change if you worked on the same data but in
?Celsius
– . No scaling has no effect on correlation
Be aware of correlationclaims
Some things may look like they are connected :but they are not
– :General knowledge and height 7 13 Children in a school from year to year are asked . general knowledge questions The correlation is worked
. out using height and their score In your opinion does ? height have any effect on their score If not can you suggest what is the explanatory factor that is connected
?to both
Outliners– As all data items are used outliners will effect the
. correlation coefficient When outliners are obvious it is .worth ignoring them altogether
- .Non linear relationships– . . . . Pearson's p m c c is only suitable for linear
relationships