Xác suất thống kê: Phân tích số lượng tử vong bởi Covid-19 ở European Union và Europe [English version]

Business Statistics – ECON1193 Assignment – Team Assignment Report - 3A Table of Content: Part 1: Data Collection (40 countries) on raw data Excel file Part 2: Descriptive Statistics Part 3: Multiple Regression Part 4: Team Regression Conclusion 10 Part 5: Time Series 11 Part 6: Time Series Conclusion 16 Part 7: Overall Team Conclusion 17 References: 18 Appendix: 20 PART 2: Descriptive Statistics Measurement of Central Tendency European Union Europe Mean 0.00020 0.00027 Median 0.00011 0.00006 Mode 0.00002 No mode Figure 1: Measures of Central Tendency for total deaths of European Union and Europe (unit: per million population) European Union Europe Minimum 0.00002 0.00001 Maximum 0.00073 0.00313 Smallest number -0.00040 -0.00017 Largest number 0.00080 0.00039 Figure 2: Outliers test for total deaths of European Union and Europe (unit: per million population) P a g e | 21 Team: Dataset - Group - Business Statistics Key findings:  The mean of total deaths in European Union (0.00020) is smaller than this value of total deaths in Europe ( 0.00027)  The median of total deaths in European Union (0.00011) is larger than this value of total deaths in Europe (0.00006)  While the mode of total deaths in European Union is 0.00002, there is no mode in Europe To commence with, according to the outliers test below, it can be seen that the outliers which is the largest number of Europe so the best measures for this case is the median because if we utilize mean, its value will be affected a lot by the extreme value and cannot cover all values On the other hand, there is no outlier in European Union; therefore, mean is the most suitable measurement in this case as this can include as many values as possible To sum up, it is obvious that the rate of total deaths in European Union is approximately equal to the value of total deaths in Europe Hence, it also illustrates that European Union countries in particular and Europe countries in general are being affected quite seriously by Covid-19 which lead to uncontrolled the number of deaths Acknowledging this, according to World Health Organization, this rate of total deaths will influence not only the economy but also significantly impact the environment; hence, the Europe group and the European Union are putting in place restoration policies to bring natural life back (World Health Organization 2020) Measurements of Variation: European Union Range (Unit: per millions population) 0.00071 Interquartile (Unit: per millions population) 0.00030 Variance (Unit: per millions population) Standard Deviation (Unit: per millions population) Coefficient Variation (Unit: per millions population) ,= < > Europe 0.00313 0.00014 < 0.00000004 0.0000005 0.00020 > 0.00069 101% < 258% Figure 3: Measures of variations for total deaths in European Union and Europe ( unit: per million population) Key findings: P a g e | 21 Team: Dataset - Group - Business Statistics  The range of total deaths in European Union is less than the range of total deaths in Europe (0.00071 and 0.00313 respectively)  The Interquartile of total deaths in European Union is greater than this value of total deaths in Europe (0.00030 and 0.00014 respectively)  The variance of total deaths in European Union is lower than the variance of total deaths in Europe (0.00000004 and 0.0000005 respectively)  The standard deviation of total deaths in European Union is bigger than this value of total deaths in Europe (0.00020 and 0.00069 respectively)  The coefficient variation of total deaths in European Union is likely less than the coefficient variation of total deaths in Europe (101% and 258% respectively) There is no doubt that Interquartile is the best measurement in this case To begin with, if we take advantage of range, it just includes two values which cannot cover every value of data in European Union and Europe Secondly, because of the outlier in Europe, variance and standard deviation formulas which include the value of mean are not suitable in this case To conclude, it claims that Interquartile is better than other measures because utilizing Interquartile, we don’t need to worry about extreme value and avoid outlier Box and Whisker Plot: Figure 4: the box and whiskers plot of total deaths in European Union (Unit: per million population) Figure 5: the box and whiskers plot of total deaths in Europe (Unit: per million population) Left side >,,