MCD1110 - DATA ANALYSIS FORMULA SHEET
Percentage Frequency
percent 
Range
count
 100%
total count
R  largest value  smallest value
Median (location)
Interquartile Range
 n 1


 2 
IQR  Q3  Q1
Lower fence  Q1  1.5IQR
Upper fence  Q3  1.5 IQR
Sample Mean
x
x
or
n
x
 xf
f
or
x
where n   f
mf
f
Sample Standard Deviation
(x  x)
2
s
n 1
or
s
or
R
s
4
 (x  x )
n 1
2
f
or
s
 (m  x )
2
f
n 1
where n   f
Standard (z) score
z
xx
s
Probability
Complement rule
P  A  P  A '   1
Addition rule
PA  B  PA  PB  PA B
Conditional probability
Multiplication rule
P  A  B   P  A  P B  (When mutually exclusive)
PA B 
P A  B
PB
P  A  B   P  B  P  A B  OR P  A  B   P  A P  B A
P  A  B   P  A P  B  When A and B are independent
P  A  P  A B  P  B   P  A B  P  B 
Law of total probability
Pearson’s Correlation Coefficient
(x  x)( y  y), where
r
n 1 sxsy
( x  x )
2
sx 
n 1
( y  y)
2
and sy 
n 1
r2
Coefficient of Determination
The Least Squares Regression Line
y  a  bx ,
where
b
rs y
sx
and
x
y
a  y  bx , where x   , y  
n
n
Time Series
3  moving mean ( smoothed y2 ) 
y1  y2  y3
3
3  moving median (smoothed y2 )  median  y1 , y2 , y3 
seasonal index 
value for season
seasonal average
deseasonalised figure 
© Monash College
actual figure
seasonal index
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