Statistics Case Study Of COVID-19 – Know the deaths across the World

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Statistics Case Study Of COVID-19 – Know the deaths across the World

Statistics

Case Study Chart on COVID-19 deaths

Abstract

COVID-19 pandemic has haunted the whole world and every study discipline is trying to examine if it can help the human race to fight against this fatal disease. Statistics has a purpose to collect digital data and analyze it to solve different problems. My project also is such an attempt to explore the solutions to the problem. This project is an interesting project in a sense that it applies statistical tools and explore solutions to an issue that is of social or medical nature: coronavirus pandemic. For this project, I selected five countries named Pakistan, Australia, Morocco, Mongolia, and Mexico to examine how differently coronavirus affected these regions of the world during the month of June. After collecting the data of affected cases and death cases from the mentioned countries, I applied statistical tools and completed descriptive statistical analysis and referential statistical analysis. Minitab software helped me a lot to do my task as a lot of work was done by just putting the figures in right way. This project reveals the underlying reasons behind varying effects of COVID-19 on different countries.

Introduction

Statistics is like a science where we collect numerical data and analyze it using vital strategies and tools. Statics appears like a complicated subject however its interesting aspects should not be undermined which help us to solve issues and enhance our intelligence as well. Famous Irish English dramatist George Bernard Shaw once said that it is the mark of a truly intelligent person to be moved by Statistics. It means that it is the analytical mind that is required to be successful in this era of smart humans. Being a student of Statistics, I was given the task by the university to do this project. The project is about a researched based study of the data about the so-called COVID-19 pandemic cases that are increasing by every moment in the world. The data was collected from the official website of the European Centre for Disease Prevention and Control. Data about COVID-19 cases and deaths due to the pandemic was collected and five countries were collected to get the data. The countries including Australia, Pakistan, Morocco, Mexico, and Mongolia were selected to collect the data. The figures about the coronavirus cases and deaths were extracted from the month of June. Thousands of people were affected by the deadly virus during the month of June and thousands of them also succumbed to death. During the practical work, different areas of Descriptive Statistics and Referential Statistics were covered. I used Minitab software to analyze the figures. In the software, I have added graphs like Pie Chart, Histogram, and Dot Plot, etc. Additionally, median, mean, and stdev, etc. also have been added to the work. Apart from that, Inferential Statistics has also been added to the project. Thus, the project is a statistical study of the COVID-19 cases in the countries like Australia, Morocco, Mongolia, Pakistan, and Mexico.

Countries Description

As it has been mentioned above that five countries were selected to collect and analyze the data. The above-mentioned countries have been briefed below.

  1. Australia

A country, an island, and a continent, Australia is everything itself. This country of around 24 million people is located between the Indian Ocean, the South Pacific Ocean and Oceania. On 1st of the June, 10 people in Australia were tested positive for COVID-19 although no death was reported due to the pandemic (Eurosurveillance Editorial Team). It was due to the measures taken by the government that the number decreased as Australia had already suffered in the month of March and April. Cases started increasing with the passage of time and 67 people were reported to be affected by the virus with zero deaths on 30th June. Total 699 cases were reported in the whole month in Australia with ony 4 fatalities.

  1. Pakistan

It is a South Asian Muslim majority state that lies between China, India, Afghanistan, Iran, and Arabian Sea. Population of Pakistan is around 220 million and 2964 people were tested positive for the virus whereas 60 people died on the 1st June. In the month of June, 139841 cases of coronavirus were reported in Pakistan.

  1. Mexico

This country of 126.2 million people is located in the southern part of North America. 3152 coronavirus cases were reported in Mexico on the starting day of June 2020; 151 deaths were also recorded. 133145 people were tested positive for COVID-19 in the whole month of June.

  1. Morocco

Morocco is a North African country and the population of the country was 36.03 million according to the World Bank statistics (Spiteri, Gianfranco, et al.). On June the 1st, 27 cases of coronavirus were recorded. 4764 was the total number of COVID-19 cases during the whole month of June.

  • Mongolia

This is a landlocked country of 3.17 million people located in East Asia and bordered by China along with Russia. Only 6 cases were reported in the country on the 1st June whereas the total number of June cases could not exceed 41.

Descriptive Statistics Summary

Practical analysis done using Minitab has been attached in Appendices segment of the project. In descriptive statistics Pie Charts were drawn to study the affected population of Australia. The attached charts show the increasing number of cases to the mid of June in Australia. The cases kept decreasing after 20th of June. Scatterplot graph was drawn to explain the situation of Mexico. The graph shows that death rate remained slower comparatively to the cases whereas the cases kept increasing. The attached Boxplot shows the number of cases in Mongolia whereas Histograms were drawn to explain the severe situation of Pakistan. In Pakistan, frequency of the cases remained high during the second week and the cases started falling during the last week. Furthermore, statistic description of Mean, Median and standard deviation has also been attached. The analysis shows that Pakistan’s case had a standard deviation of 1110 whereas Mean was 4661. Where the death cases were concerned, Standard Deviant remained at 28.50 and Mean at 94.03. It means that deaths remained too low than the cases.

Apart from Pakistan, Mexico is another country which faced surge in coronavirus cases. The descriptive analysis shows that Standard Deviation was 900 inn terms of cases and 246.0 in terms of deaths. Additionally, the document also reveals the Median rate that was 4426 in terms of cases and 599.0 in terms of fatalities. Australian figures were comparatively low and these figures were nearer to the other selected countries like Mongolia and Morocco (Stoecklin, Sibylle Bernard, et al.). The figures reveal that Cases’ Mean was 19.40 whereas Deaths’ Mean was 0.0667. Median remained at 14.00 in terms of Cases and fell to 0.0000 in terms of deaths. Thus, Australian figures were much satisfactory than other countries like Pakistan and Mexico.

Inferential Statistic Summary

Samples from the countries like Pakistan and Mexico were selected to analyze the potential of COVID-19 outbreak. Let us discuss the Confident Interval about the number of affected cases and the number of death cases. One hypothesis was rejected and labelled as a null hypothesis to study the population of Pakistan. The null hypothesis said that the difference of deaths and cases was equal to zero. After doing a confidence interval analysis it was proved that it was not like that. See below:

Null hypothesisH₀: μ₁ – µ₂ = 0
Alternative hypothesisH₁: μ₁ – µ₂ ≠ 0
T-ValueDFP-Value 
22.52290.000 

The hypothesis reveals that the difference was proved unequal to zero. SE Mean was 203 in terms of affected cases and 5.2 in terms of fatalities (World Health Organization. Modes of transmission of virus causing COVID-19). Confident Interval was 95%. So, putting the analysis into simple language, it is known that the affected rates are not certain to death rates nor are the death rates. The both figures are unequal and they run differently.

Reviewing the analysis of Mexican figures, the same kind of hypothesis is considered null and the results are the same with same accuracy. Now, you can understand that the affected cases do not certainly determine the death cases. However, some other factors do. For instance, Australia faced a lower number of cases, but the fatality rate was zero. The other involved factors could be good medical facilities and better immune system. To understand this factor, let us compare the figures of Pakistan and Mexico. 2964 Pakistanis were tested positive for COVID-19 on the 1st June however number of the affected Mexicans was 3152. However, 3 times more Mexicans were died of the pandemic than Pakistanis despite the fact that Pakistan does not has a strong health sector like Mexico (Eurosurveillance Editorial Team). This fact shows that Pakistanis survived the pandemic perhaps because they had a stronger immune system. Applying this to the world, it can be assumed that arming masses with stronger immune system can save more people than vaccines.

Limitations

All the data for the project was collected from the website of the European Centre for Disease Prevention and Control (ECDPC). For a more reliable research, the researcher should interact with at least a few members of the target population (Heymann, David L., and Nahoko Shindo). However, I relied on the already available data and I chose diverse population majority of which is somehow alien to me. This is the limitation of this study that I analyzed a population however I have least experience to interact with the target population. Moreover, all my analysis was made with the help of Minitab software that might have some hidden errors and that also might have affected the analysis. The next researchers should consider these factors before starting a project.

Conclusion

Statistics helps us analyzing numeric data with certain tools. Tools in the contemporary era are made and used with the help of Information Technology. I used the tool called Minitab software to do my analysis. Five countries including Mexico, Pakistan, Mongolia, Australia, and Morocco were selected to collect and analyze the data. Two countries per say Pakistan and Mexico were the most affected countries by COVID-19 pandemic in June whereas the other countries faced comparatively lower number of cases. Descriptive statistical analysis and referential statistic analysis were made. In the descriptive analysis, different graphs were used to explain the figures about the selected countries. The figures of Australia were presented in Pie Chart that showed the surge of cases during the mid of the month and then sudden fall. Cases in countries like Pakistan and Mexico kept increasing day by day as the graphs like Histogram and Dot plot show. All the practical work was done in Minitab software and all the practical works has been attached in the Appendices part of this assignment. In the descriptive analysis, different terms like Mean, Median, and Standard Deviant were also applied in the work. Furthermore, inferential statistic method was also implied. Certain hypotheses were considered null and the claim was proved successfully with 95% confidence. For instance, the hypothesis that difference in affected cases and death case is zero was considered null and then it was proved the same way. I believe that COVID-19 is affecting different communities in different ways and better immune system as well as better healthcare facilities determine the fall in COVID-19 cases and fatalities. However, the new researchers should consider limitation to my study that appeared because I relied on the available data and did not interact even a single person from the target populations. The future analysts are advised to address such issues in advance.

References

Eurosurveillance Editorial Team. “Updated rapid risk assessment from ECDC on the novel coronavirus disease 2019 (COVID-19) pandemic: increased transmission in the EU/EEA and the UK.” Eurosurveillance 25.10 (2020).

World Health Organization. Modes of transmission of virus causing COVID-19: implications for IPC precaution recommendations: scientific brief, 27 March 2020. No. WHO/2019-nCoV/Sci_Brief/Transmission_modes/2020.1. World Health Organization, 2020.

Stoecklin, Sibylle Bernard, et al. “First cases of coronavirus disease 2019 (COVID-19) in France: surveillance, investigations and control measures, January 2020.” Eurosurveillance 25.6 (2020): 2000094.

Spiteri, Gianfranco, et al. “First cases of coronavirus disease 2019 (COVID-19) in the WHO European Region, 24 January to 21 February 2020.” Eurosurveillance 25.9 (2020): 2000178.

Heymann, David L., and Nahoko Shindo. “COVID-19: what is next for public health?.” The Lancet 395.10224 (2020): 542-545.

Eurosurveillance Editorial Team. “Latest updates on COVID-19 from the European Centre for Disease Prevention and Control.” Eurosurveillance 25.6 (2020).

Appendixes

Appendix I

(Bar Graph for Cases)

Chart of Deaths

(Bar Graph for Deaths)

Appendix II

Stem-and-leaf of Cases   N = 30

5012234
(13)05667777888899
12103
1017789
6234
429
33 
33 
343
24 
253
15 
164

Leaf Unit = 10

Stem-and-leaf of Deaths   N = 30

Two Sample T- Test and CI: Cases, Deaths

Method

μ₁: mean of Cases
µ₂: mean of Deaths
Difference: μ₁ – µ₂

Equal variances are not assumed for this analysis.

Descriptive Statistics

SampleNMeanStDevSE Mean
Cases3046611110203
Deaths3094.028.55.2

Estimation for Difference

Difference95% CI for
Difference
4567(4153, 4982)

Test

Null hypothesisH₀: μ₁ – µ₂ = 0
Alternative hypothesisH₁: μ₁ – µ₂ ≠ 0
T-ValueDFP-Value 
22.52290.000 
  • Appendices

Two Sample T-Test and CI: Pakistan, Mexico: CASES

Method

μ₁: mean of Pakistan
µ₂: mean of Mexico
Difference: μ₁ – µ₂

Equal variances are not assumed for this analysis.

Descriptive Statistics

SampleNMeanStDevSE Mean
Pakistan3046611110203
Mexico304438900164

Estimation for Difference

Difference95% CI for
Difference
223(-300, 746)

Test

Null hypothesisH₀: μ₁ – µ₂ = 0
Alternative hypothesisH₁: μ₁ – µ₂ ≠ 0
T-ValueDFP-Value 
0.86550.396 

Two Sample T-Test and CI: Pakistan, Mexico: DEATHS

Method

μ₁: mean of Pakistan
µ₂: mean of Mexico
Difference: μ₁ – µ₂

Equal variances are not assumed for this analysis.

Descriptive Statistics

SampleNMeanStDevSE Mean
Pakistan3094.028.55.2
Mexico3057824645

Estimation for Difference

Difference95% CI for
Difference
-484.0(-576.5, -391.6)

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