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8/10/2019 Jing Chen Statistics
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Professor King
MA336
Jing Chen
Analysis
The Histogram is pretty strong right skewed.This is because the
frequency of the values
are tend to the lower end.
The five-number summary was as follows:
Minimum : 418.7
Q1: 1301.3
Q2/ Median: 1113
Q3: 2307
Maximum: 15290
Mean: 2254.18
What this tells me about there is a relatively small spread
between the three quartiles, but
there is very large maximum and very low minimum.What this tells
me about there must be
outliers.The mean is much closer to the higher end of the data
or quartile 3. That is because
there must be some kind of outlier on the bigger end, therefore
the 15290 maximum.
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8/10/2019 Jing Chen Statistics
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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 yintercept
a is the slope
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8/10/2019 Jing Chen Statistics
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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.
