Python Data - Assignment 2 Questions

Question 4 (10 marks)

Use the dataset billionaire.xlsx to answer the following questions. The dataset contains the following variables: Nation (country name), Number (number of billionaire), GDP (in billions USD), and Population (in millions).

1. Obtain the median of GDP per capita: GDP_pc = GDP/Population, and use the median of GDP_pc to make countries into two groups: "Rich" (countries with GDP per capita above the median) and "Not_Rich" (countries with GDP per capita equal to or below the median). Find the mean number of billionaires for each group & use the barplot of Seaborn to plot these two means. Comment on the results and discuss if the two CI's are "symmetric around the mean value".
2. Let the mean number of billionaires of the Rich group as "meanN-Rich" and the mean number of the Not_Rich group as "meanN-Not_Rich". Show that none of the following two null hypotheses (i) meanN-Rich = meanN-Not_Rich (ii) meanN-Rich = 2 * meanN-Not_Rich can be rejected at 10% significance level. Discuss what might contribute to the non-rejections.
3. Obtain two scatter plots with fitted lines: Number vs. GDP and Number vs. GDP per capita. Test if (i) Number and GDP are correlated and (ii) Number and GDP per capita are correlated. Comment on the results.
4. Estimate the following two multiple regressions: (i) Number on GDP and Population (ii) Number on GDP per capita and Population. Compare and comment on the results of the two regressions.
5. Use the scatterplot to visualize the fitness of two regression predictions from Part 4 (as in Topic 8). Discuss the role of the United States in the fitness.

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