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1 Statistical Analysis of CO2 Emissions and Dairy Production Echo 03 - 13 - 2024 2 Introduction In this project, we will analyze the relationship between CO2 emissions and dairy production across various countries using s tatistical techniques. Data The data provided includes CO2 emissions (in tonnes) and dairy production (in tonnes) for several countries. Country CO2 Emissions (t) Dairy Production (t) Russia 2,010,000,000 32,330,000 Canada 655,620,000 9,470,000 USA 5, 160,000,000 102,650,000 China 12,240,000,000 41,250,000 Algeria 182,170,000 3,260,000 Mexico 807,690,000 13,070,000 Colombia 133,490,000 6,790,000 Brazil 1,660,000,000 36,660,000 Vietnam 605,470,000 1,100,000 Thailand 306,550,000 1,200,000 Argentin a 220,730,000 11,550,000 Cuba 12,110,000 384,000 Saudi Arabia 635,290,000 2,920,000 Somalia 21,090,000 2,180,000 South Africa 425,930,000 3,840,000 Australia 380,450,008 8,860,000 Japan 1,070,000,000 7,590,000 Turkey 418,460,000 23,200,000 Germany 670,440,000 33,190,000 Norway 48,660,000 1,600,000 Romania 57,960,000 4,300,000 France 290,020,000 25,830,000 Sweden 44,040,000 2,780,000 New Zealand 36,890,000 21,890,000 India 2,730,000 208,980,000 Myanmar 131,250,000 2,150,000 Iran 674,850,000 7 ,850,000 Philippines 167,480,000 16,080 Poland 293,900,000 14,890,000 Spain 210,310,000 8,700,000 Description of Data Groups We have two data groups: 1. CO2 Emissions: This represents the amount of CO2 emissions in tonnes for each country. 3 2. Dairy Producti on: Represents the amount of dairy production in tonnes for each country. Histograms: Boxplots 4 Sample Mean and Standard Deviation • Sample mean for CO2 emissions: x ˉCO2 =985,786,000 tonnes • Sample standard deviation for CO2 emissions: s CO2 =2,34 1,179,104 tonnes • Sample mean for dairy production: x ˉdairy =21,349,336 tonnes • Sample standard deviation for dairy production: s dairy =40,862,578 tonnes 5 Confidence Interval: Variable Sample Mean Standard Deviation Sample Size Confidence Level M argin of Error CO2 Emissions 837,764,788.45 2,341,179,104 30 95% =CONFIDENCE(0.05, 2341179104, 30) Dairy Production 14,622,217.05 40,862,578 30 95% =CONFIDENCE(0.05, 40862578, 30) Two - Sample T - Test: Since we don't have paired data, we will not conduct a paired t - test. However, we can conduct a two - sample t - test to compare the means of CO2 emissions and dairy production between two groups of countries. Formula for Two - Sample T - Test: =T.TEST(array1, array2, tails, type) =T.TEST(E3:E32, D3:D32, 2, 3) Two - Sample T - Test = 0.031781436 Conclusion: 1. Statistical Significance: • Evidence: The confidence interval and hypothesis test results indicate a statistically significant difference between mean CO2 emissions and dairy production. 2. Consistency between Confidence Interval and Hypothesis Test: • Evidence: The confidence interval and hypothesis test reached the same conclusion. This alignment is a core principle in statistical analysis; it underlines our findings' robustness, reinforcing their validity. 3. Conn ection between Descriptive and Inferential Statistics: • Evidence: Boxplots and histograms, among other descriptive statistics, visually represent data distributions and characteristics. Such visuals offer valuable insights into the spread and central tenden cy of CO2 emissions and dairy production. 6 • Further Evidence : Inferential statistics, including confidence intervals and hypothesis tests, quantify uncertainty; they evaluate the significance of observed differences. Through this process, we can draw populat ion - based conclusions from sample data. 4. Surprising Findings: • Evidence: The mean CO2 emissions and dairy production across the countries studied exhibited a surprisingly substantial difference. Such discrepancy implies notable variations in environmental im pact and agricultural output, thus prompting inquiries into the underlying factors; moreover, it underlines their potential implications for policy formulation and sustainability initiatives. 5. Additional Research and Questions: • Evidence: Based on our results, additional research is warranted to explore the drivers of CO2 emissions and dairy production, their environmental and economic impacts, and potential mitigation strategies. • Further Evidence: Investigating regional variation s and trends could provide valuable insights for designing targeted interventions and promoting sustainable development on a global scale.