Statistics to Technology Problems: Analysis Report, University of XYZ

This report presents a statistical analysis investigating the relationship between CO2 emissions and per capita GDP. The study identifies the problem of increasing CO2 levels and its impact on the global environment, using data from the Joint Research Centre (EDGAR) and the World Bank for the year 2016. The analysis employs central tendency and descriptive statistics, utilizing Microsoft Excel for data processing. The report includes data tables and a regression analysis, concluding that there is a positive correlation between a country's GDP and its CO2 emissions. The findings emphasize the need for sustainable development models to mitigate environmental concerns while considering economic stability. The report recommends that global governing bodies and the general population work towards sustainable practices to reduce CO2 emissions and protect the environment. The report also includes a bibliography and an appendix with the dataset used for analysis.

Running head: STATISTICS TO TECHNOLOGY PROBLEMS
Statistics to Technology Problems
Name of the Student:
Name of the University:
Author Note

1
STATISTICS TO TECHNOLOGY PROBLEMS
Part B: Statistical Analysis
Task 1:
The problem identified for this analysis requiring statistical application is the level of
CO2 that is generated per capita is related to the GDP of the country. When the CO2 level of
the country goes up the overall CO2 Level of the word also goes up and this is hampering the
atmosphere to a great extent and hence, measures are required to be taken for avoiding the
calamities that might follow. We need to find the relationship in between the per capita
income of the country and the Level CO2 released from the country. It is to be checked
weather in situation where income level of a country goes up the Co2 Emission level also
goes up.
Task 2:
The CO2 emission per capita has been used for the analysis in this discussion. The
data is collected from Joint Research Centre (EDGAR). Emission Database for Global
Atmospheric Research. The most recent data available was 2016 and hence, the data was
collected for analysis. The per capita income of the countries has been used in the analysis.
The data has been gathered from the World bank. The available data for the year 2016 was
considered for the analysis (Data.worldbank.org, 2018).
Task 3:
It has already been identified that as the per capita income increases and the emissions
increases, however it has been identified that it tends to decelerate for the most parts. The
increasing income level results in the increasing the demands for environment protection. The
main aim is not only to reduce the level of emission to the proposed level but also it is to be
kept in mind that the less developed countries are not affected adversely.

2
STATISTICS TO TECHNOLOGY PROBLEMS
Task 4:
The statistical techniques to be applied for the analysis are central tendency and
descriptive statistics. The central tendency for the random variable for clustering around its
mean, median and mode. The Descriptive statistics techniques has been used here for the
description of the basic features of the data gather for analysis in this discussion. A simple
summary about the sample and the measures are to the gathered here. The quantitative
analysis of data is obtained here.
Task 5:
Microsoft Excel is used here for the analysis of data gathered and computing those
data using the automated functions provide in Microsoft Excel.
Task 6:
The data collected for the analysis is provided in the appendix
(Edgar.jrc.ec.europa.eu, 2018).
Task 7:
The data provided by the Joint research centre was very complete and all the data for
each country was presented efficiently. The data provided on the website of the research
centre ranged from the year 1990 to 2016. However, for specifying the time period only the
most recent data was selected which was 2016. In the per capita income data there were data
which were missing for some of the countries. Hence, the data was filtered so that the sample
did not include any null values.
Task 8:
The business problem is predicting the CO2 emission of a country from per capita.
(Coefficients + Intercept) * Ton CO2/1000$.

3
STATISTICS TO TECHNOLOGY PROBLEMS
Task 9:
Coefficients Standard Error t Stat P-value
Intercept 12942.89292 2486.062948 5.206180692 6.62968E-07
Ton CO2/1000$ -3605.979998 8279.341633 -0.435539462 0.663832223
Task 10:
From the above analysis it can found that with increase in GDP of a particular country
The CO2 emission of the country also increases.
Task 11:
It is to be addressed to the general population and the governing bodies of the
countries of the world that the outcome means that the increase in CO2 level is a huge
concern for the global environment but, the solution to this might hamper the economy of
countries that are facing though challenge to acquire a steady position. Hence, it is
recommended that all the nations across the world move for the sustainable development
model.
Task 12:
Data Analysis tool pack of excel sheet has been used for obtaining the results.

4
STATISTICS TO TECHNOLOGY PROBLEMS
0 20000 40000 60000 80000 100000 120000
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Ton CO2/1000$

5
STATISTICS TO TECHNOLOGY PROBLEMS
Bibliography
Data.worldbank.org. (2018). GDP per capita (current US$) | Data. [online] Available at:
https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?end=2017&start=2014 [Accessed 5
Dec. 2018].
E dgar.jrc.ec.europa.eu. (2018). EDGAR - Fossil CO2 & GHG emissions of all world
countries, 2017 - European Commission. [online] Available at:
http://edgar.jrc.ec.europa.eu/overview.php?v=CO2andGHG1970-2016&dst=CO2gdp
[Accessed 5 Dec. 2018].

6
STATISTICS TO TECHNOLOGY PROBLEMS
Appendix
Co2 emission per GDP (2016)
Country Ton CO2/1000$ GDP per Capita
Afghanistan 0.16 561.7787463
Angola 0.18 3308.772828
Albania 0.16 4131.872341
Argentina 0.37 12654.355
Armenia 0.19 3605.743117
Antigua and Barbuda 0.21 14462.17628
Australia 0.39 49896.6811
Austria 0.19 44731.01086
Azerbaijan 0.22 3880.738731
Burundi 0.14 285.7274421
Belgium 0.2 41260.97755
Benin 0.3 788.5324424
Burkina Faso 0.08 613.9931275
Bangladesh 0.14 1358.779029
Bulgaria 0.4 7469.447703
Bahrain 0.39 22560.58127
Bosnia and Herzegovina 0.65 4808.636043
Belarus 0.39 5022.626643
Belize 0.39 4960.181794
Brazil 0.16 8639.365743
Barbados 0.35 15891.62655

7
STATISTICS TO TECHNOLOGY PROBLEMS
Brunei Darussalam 0.25 26939.41805
Bhutan 0.26 2773.547135
Botswana 0.18 6954.174306
Canada 0.43 42348.94546
Chile 0.2 13960.89421
China 0.52 8117.267465
Cote d'Ivoire 0.12 1535.068121
Cameroon 0.13 1374.515899
Colombia 0.12 5756.861602
Cabo Verde 0.03 3037.525642
Costa Rica 0.11 11732.71055
Cyprus 0.26 23541.48825
Germany 0.21 42232.57421
Djibouti 0.49 1872.234623
Dominica 0.25 7906.721742
Denmark 0.15 53578.75657
Algeria 0.28 3916.881571
Ecuador 0.23 6018.526868
Estonia 0.61 17736.8027
Ethiopia 0.06 712.87795
Finland 0.24 43433.03222
Fiji 0.21 5197.50914
Gabon 0.17 7078.68326
Georgia 0.25 3865.785694
Ghana 0.13 1517.495508

8
STATISTICS TO TECHNOLOGY PROBLEMS
Guinea 0.14 748.3013059
Guinea-Bissau 0.12 648.8989366
Equatorial Guinea 0.07 9217.889528
Greece 0.26 17881.5267
Grenada 0.4 9841.76405
Greenland 0 48159.53471
Guatemala 0.15 4140.737635
Guyana 0.58 4531.243527
Honduras 0.23 2375.096327
Croatia 0.22 12298.57035
Haiti 0.17 734.8025912
Hungary 0.2 12820.0882
Indonesia 0.19 3570.284615
India 0.31 1717.473878
Ireland 0.13 64100.42995
Iraq 0.27 4609.600694
Iceland 0.26 60529.92676
Jamaica 0.38 4878.575791
Jordan 0.29 4087.937517
Japan 0.26 38972.34064
Kazakhstan 0.56 7714.841844
Kenya 0.12 1462.505115
Cambodia 0.12 1269.907238
Kiribati 0.24 1587.058145

9
STATISTICS TO TECHNOLOGY PROBLEMS
Kuwait 0.36 27368.28668
Lebanon 0.28 8257.294391
Liberia 0.24 455.3707414
Libya 1.15 5125.675283
Sri Lanka 0.08 3857.396363
Lesotho 0.05 1039.703303
Lithuania 0.17 14912.68654
Luxembourg 0.18 100738.6842
Latvia 0.18 14070.42265
Morocco 0.22 2892.775561
Madagascar 0.09 401.7422654
Maldives 0.24 9871.906911
Mexico 0.21 8443.691924
Mali 0.05 779.9448438
Malta 0.14 24770.80657
Myanmar 0.06 1195.515372
Mongolia 0.54 3694.082552
Mozambique 0.18 382.069457
Mauritania 0.17 1101.901529
Mauritius 0.13 9681.618567
Malawi 0.09 300.3076651
Malaysia 0.33 9508.23775
Namibia 0.16 4560.70206
New Caledonia 0.43 0

10
STATISTICS TO TECHNOLOGY PROBLEMS
Nigeria 0.08 2175.673442
Nicaragua 0.17 2143.925893
Norway 0.13 70890.03557
Nepal 0.12 729.1222515
New Zealand 0.2 40331.9591
Oman 0.5 15102.38231
Pakistan 0.19 1442.28584
Panama 0.13 14332.97248
Peru 0.15 6031.366091
Palau 0.14 14077.09622
Papua New Guinea 0.41 2461.945636
Poland 0.3 12415.04329
Puerto Rico 0.01 30833.37247
Portugal 0.18 19871.71897
Paraguay 0.1 4077.742071
French Polynesia 0.18 0
Qatar 0.33 59324.33877
Romania 0.18 9532.167174
Rwanda 0.07 711.1957913
Saudi Arabia 0.32 19982.08563
Senegal 0.22 952.7715367
Singapore 0.11 55243.13288
Solomon Islands 0.28 2056.489935
Sierra Leone 0.13 480.7930211

11
STATISTICS TO TECHNOLOGY PROBLEMS
El Salvador 0.14 3768.837705
Somalia 0.21 471.6199878
Sao Tome and Principe 0.09 1771.987941
Suriname 0.29 5871.442003
Slovenia 0.24 21650.21276
Sweden 0.1 51844.76126
Seychelles 0.21 15060.99099
Chad 0.06 651.2372438
Togo 0.22 576.9594785
Thailand 0.25 5979.293546
Tajikistan 0.25 795.8438644
Turkmenistan 0.89 6389.334143
Timor-Leste 0.21 1987.124857
Tonga 0.44 3748.641794
Trinidad and Tobago 0.87 16352.10973
Tunisia 0.24 3688.646375
Turkey 0.2 10862.72538
Uganda 0.07 580.383534
Ukraine 0.71 2185.728031
Uruguay 0.09 15298.35089
Uzbekistan 0.57 2105.870905
Vanuatu 0.18 2913.967232
Samoa 0.15 4030.013144
South Africa 0.57 5280.017633