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P r o f e s s o r K i n g
M A 3 3 6
J i n g C h e n
A n a l y s i s
T h e H i s t o g r a m i s p r e t t y s t r o n g r i g h t s
k e w e d . T h i s i s b e c a u s e t h e f r e q u e n c y o f t
h e v a l u e s
a r e t e n d t o t h e l o w e r e n d .
T h e f i v e - n u m b e r s u m m a r y w a s a s f o l l o w
s :
M i n i m u m : 4 1 8 . 7
Q 1 : 1 3 0 1 . 3
Q 2 / M e d i a n : 1 1 1 3
Q 3 : 2 3 0 7
M a x i m u m : 1 5 2 9 0
M e a n : 2 2 5 4 . 1 8
W h a t t h i s t e l l s m e a b o u t t h e r e i s a r e l a
t i v e l y s m a l l s p r e a d b e t w e e n t h e t h r e e q u
a r t i l e s , b u t
t h e r e i s v e r y l a r g e m a x i m u m a n d v e r y l o
w m i n i m u m . W h a t t h i s t e l l s m e a b o u t t h e r e
m u s t b e
o u t l i e r s . T h e m e a n i s m u c h c l o s e r t o t h
e h i g h e r e n d o f t h e d a t a o r q u a r t i l e 3 . T h a
t i s b e c a u s e
t h e r e m u s t b e s o m e k i n d o f o u t l i e r o n t h
e b i g g e r e n d , t h e r e f o r e t h e 1 5 2 9 0 m a x i m u
m .
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According to my data, there are two outlier . The two outliers
are the United States and
China . The Electricity Production for the United States was
3953bn and the electricity
production for China was 4604bn . The Gross Domestic Product for
the United States was
15290bn and the Gross Domestic Product for China was 11440bn .
The reason those two outlier
is because the United States is one of the richest countries,
making its electricity production
extremely high . As for China, it is so large geographically and
has such a large population that
its electricity production must be high .
My analysis of the data shows that there is an extremely strong
correlation between
Electricity production (x) and the Gross Domestic Product (y)
for each nation . The R Squared, or
coefficient of determination indicates this point . The closer
the R Squared value is to 1,
obviously it is stronger the correlation . In this case, the R
Squared value is .916257 which is
equal to 91 .6257% . If something between 70 to 100% is usually
considered to have a strong
correlation .
The linear regression trend line that I found was y = 519 .9 + 2
.99x .
The regression line I derived was from the formula, y = b + ax
.
x is the Electricity Production (in Bn)
y is the GDP (in Bn)
b is the y intercept
a is the slope
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What the regression line makes me think about and predict a GDP,
given any value of electricity
consumption . The value of R square is .916257, the prediction
of the GDP will be very accurate .
For example, I plugged one number from the (x) value which is
the electricity consumption for
France, 510 . The value I got for the Gross Domestic Product was
2044 .8, as we can see actual
GDP is 2246 .
I think my predictions will be very accurate . This is because
of the R Square value . The
higher the r square value, As a result, it is very easy to using
the linear regression line to predict.
In my conclusion, I think there is an extremely high correlation
between the production
of electricity and Gross Domestic Product.
