Statistics and Data Analysis

Statistics and Data Analysis 1
Statistics and Data Analysis
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Statistics and Data Analysis 2
Statistics and Data Analysis
Burgernomics
a) The puzzle from the theoretical perspective of Burgernomics based on the findings of the
Big Mac Index 2016
We observe that Switzerland, Sweden and Norway have currencies which are stronger that the
US dollar which then means higher prices for the hamburger. Based on the July 2014 and
January 2016 data, the currency of some few countries such as Venezuela, Norway and Brazil
had their currencies weaken in a higher rate compared to the others. Other countries such as
Hong Kong, U.A.E and China had a more stable currency over that period. Almost in all the
countries, the currencies have weakened against the US dollar except the Indian which has a
slight growth. Also, fewer countries such as Venezuela, Brazil and Canada had a stronger
currency against the dollar by July 2014 and it grew weaker below the dollar by January 2016.
Venezuela had the widest change of the currency strength between these two time points and this
might have been affected by several factors such as the political stability which leads to
economic sabotage.
Generally, the findings of Mac Index in 2016 indicates that as the currency of a country weakens
against the dollar, so does the price of a hamburger and vice versa. From the forest plot, we
observe clear proportionality of the price and the strength of the local currency. To interpret, it
can be inferred that a hamburger would cost higher in countries with stringer economies
compared to their counterparts. Further, we would infer that the price of the hamburger is much
influenced by the current strength of the currency other than its progression. For instance, from
the Mac Index 2016 findings, we would see that currency of some countries such as Norway
were very strong against the dollar in 2014, but comparing with Sweden whose currency is more
stable, the change does not affect hamburger pricing. Therefore, these findings affirm that the
current purchasing power parity (PPP) of a customer, which is highly influenced by the strength
of a country against the dollar, influences hamburger price. The puzzle would then be, if it has
been assumed by the hamburger recipe does not change much across countries, might there be
other factors influencing the price of the hamburger or the purchasing power parity.
b) Using the 2017 Human development Index (HDI)
In this dataset, the components of HDI include life expectancy at birth, expected years of
schooling, mean years of schooling, gross national income (GNI) per capita and difference
between GNI per capita rank and the HDI rank. The HDI index can also be used to reflex the
purchasing power parity because it comprises of quality of life, knowledge and standard of
living, which are also estimated based on the strength of the currency against the standard (US
dollar). Therefore, using the 2017 HDI data, we can infer the puzzle and the possible factors and
components influencing the PPP.
Hypothesis
Based on the 2017 HDI data, we would hypothesize that life expectancy, expected years and
mean years of schooling and GNI significantly influence the HDI index. In details, we
hypothesize that there is a strong positive correlation between HDI index and the outlined
potential explanatory variables.

Statistics and Data Analysis 3
As shown in table 1, it is observed that the average HDI index in the 189 countries is 0.709 with
a standard error of 0.01. The skewness statistic infers that most of the countries have HDI index
lower than the average.
Table 1: Summary statistics for the HDI index
HDI
Mean 0.709
Standard Error 0.011
Median 0.735
Standard Deviation 0.153
Sample Variance 0.023
Kurtosis -0.826
Skewness -0.379
Range 0.599
Minimum 0.354
Maximum 0.953
Count 189
Confidence Level (95%) 0.022