ECON 1030 - BUSINESS STATISTICS 1 GROUP ASSIGNMENT (Friday Tutorial) Marks: 20 Due: 29 May at 11:59 PM (Week 12) Instructions: This is an optional group assignment with a minimum group size of one and a maximum group size of three. All group members will receive the same marks for the assignment. All group members must be enrolled in the same tutorial. The assignment must be provided in the form of a (brief) business report approximately 6-10 pages (including this cover page). You must submit an electronic copy of your assignment in Blackboard. Hard copies will not be accepted. SHOW YOUR WORK for Calculation based questions if you wish to receive partial credit. This assignment requires the use of Microsoft Excel. If you have Windows, you will also need to use the Data Analysis ToolPak. If you have a Mac with Excel 2011, you will need to use StatPlus:MAC LE. Group Members: First name Last name Please indicate your tutor and tutorial time: Tutor Tutorial date and time Student ID Problem Description: As the world continues to develop, The World Bank is conducting a new study to determine whether the link between life expectancy and income remains strong. They have collected data on 54 developing countries across the globe and have reported data on life expectancy (on years from birth), the percent of the population with HIV, Income ($000s), literacy rate of adults 15 years and older, as well as a set of dummies indicating the region that the country is located in. You will use descriptive statistics, inferential statistics and your knowledge of multiple linear regression to complete this task. le (Dependent Variable) and several characteristics (Independent Variables) are given in the Excel file: Friday.xlsx. Here is a table describing the variables in the data set: Variable Le hiv Income Literacy Americas Europe AsiaPacific Africa Definition Life Expectancy in years from birth Percent of the population that is HIV positive or living with AIDS Per Capita Income of country in $000s of US$ Literacy rate of adults 15 years and above Dummy variable indicating country is in North or South America Dummy variable indicating country is in Europe Dummy variable indicating country is in Asia-Pacific Region Dummy variable indicating country is in Africa Required: A. Calculate the descriptive statistics from the data and display in a table. Be sure to comment on the central tendency, variability and shape for each variable. (1 Mark) B. Draw a graph that displays the distribution of life expectancy. (1 Mark) C. Create a box-and-whisker plot for the distribution of share of population with HIV and describe the shape. Is there evidence of outliers in the data? (1 Mark) D. What is the likelihood that a country has a life expectancy above 65 if per capita income is below US$1000? Is per capita income independent of life expectancy? Use a Contingency Table. (2 Marks) E. Estimate the 95% confidence interval for the population mean literacy rate. (1 Mark) F. Your supervisor recently stated that life expectancy in Africa is below the average developing country of 67 years. Test her claim at the 10% level of significance. (1 Mark) G. Run a multiple linear regression using the data and show the output from Excel. Hint: For the multi-level categorical variables, compare the Americas, Europe, AsiaPacific to Africa. (1 Mark) H. Is the coefficient estimate for per capita income different than zero at the 5% level of significance? Set-up the correct hypothesis test using the results found in the table in Part (G) using both the critical value and p-value approach. Interpret the coefficient estimate of the slope. (2 Marks) I. Interpret the remaining slope coefficient estimates. Comment on whether the signs are what you are expecting. (2 Marks) J. Interpret the value of the Adjusted R 2. Is the overall model statistically significant at the 1% level of significance? Use the p-value approach. (1 Mark) K. Do the results suggest that the data satisfy the assumptions of a linear regression: Linearity, Normality of the Errors, and Homoscedasticity of Errors? Show using scatter diagrams, normal probability plots and/or histograms and Explain. (3 Marks) L. Based on the results of the regressions, is it likely that other factors have influenced the life expectancy? If so, provide a couple possible examples and indicate whether these would likely influence the regression results if they were included. (1 Mark) M. If a community housing organisation asked for information regarding the characteristics of housing targeting the households of native-born Australians, explain whether a clustered sampling technique of the CBD would provide an accurate representation of these households. (Note: This question does not use the data) (1 Mark) Allocation of Marks: Professional Business Report Part A Part B Part C Part D Part E Part F Part G Part H Part I Part J Part K Part L Part M Total: 2 Marks 1 Mark 1 Mark 1 Mark 2 Marks 1 Mark 1 Mark 1 Mark 2 Marks 2 Marks 1 Mark 3 Marks 1 Mark 1 Mark 20 Marks country le Angola Argentina Armenia Bangladesh Botswana Bulgaria Cape Verde Chad Colombia Comoros Costa Rica Cote d'Ivoi Croatia Ecuador Egypt Equatorial Eritrea Estonia Gabon Gambia Georgia Greece Guatemala Guinea-Bis Hungary Indonesia Italy Latvia Lithuania Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Nepal Papua New Poland Portugal Romania Serbia Sierra Leon Slovenia South Afric Sudan Swaziland Tajikistan Togo hiv 60.4 76 73.8 69.5 65.8 74.5 74.2 57.1 75.6 63.7 79.8 58.9 77.8 74.8 70.9 58.8 62.1 76.6 59.1 64.3 72.9 79.8 72.3 52.8 75.8 70.5 82.1 75.3 75 57.2 65.1 73.3 75.5 71.9 64.7 74.3 70.6 59.8 76.9 79.8 76 77.7 57.7 80 60.4 68.9 50.7 70.6 63 2.1 0.4 0.2 0.06 23.4 0.1 1 3.1 0.5 0.1 0.3 3 0.06 0.4 0.06 4.7 0.6 1.3 5 1.5 0.2 0.2 0.8 2.5 0.1 0.3 0.4 0.7 0.1 1.1 1.1 1 0.2 0.5 0.06 0.2 0.3 0.7 0.1 0.7 0.1 0.1 1.6 0.1 17.3 0.4 26 0.3 3.4 income literacy Americas Europe 0.629955 70.3624 0 11.6016 97.8588 1 1.38409 99.5682 0 0.588369 57.7348 0 4.37756 85.0909 0 2.61888 98.3524 0 2.03888 84.9363 0 0.301402 35.3915 0 3.36247 93.5805 1 0.335219 75.5398 0 5.3678 96.258 1 0.548231 56.8675 0 6.27004 98.8807 0 1.83701 91.5869 1 1.97661 72.9567 0 8.87514 94.2259 0 0.15481 68.9374 0 6.52554 99.7969 0 4.33381 88.9889 0 0.614912 51.1073 0 1.33465 99.7325 0 12.509 97.3018 0 1.88642 75.8573 1 0.166347 55.2752 0 5.74598 99.0472 0 1.20699 92.8119 0 18.9373 98.9797 0 5.33057 99.7842 0 5.79329 99.7036 0 0.272309 33.4412 0 0.623374 58.6139 0 5.37083 88.8472 0 6.28825 93.52 1 0.635506 98.9708 0 0.893992 97.3559 0 1.9083 67.0842 0 0.274873 57.3691 0 0.793198 62.4217 0 6.85446 99.7302 0 11.5519 95.4341 0 2.63302 97.7019 0 1.22364 98.0129 0 0.278243 43.2831 0 12.6887 99.695 0 3.82509 92.9831 0 0.561843 71.9378 0 1.81354 87.8443 0 0.29536 99.7071 0 0.273107 60.4099 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 1 0 1 1 1 0 0 0 0 1 0 0 0 0 1 1 1 1 0 1 0 0 0 0 0 AsiaPacific Africa 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 1 0 1 0 1 0 0 1 1 1 0 1 1 0 0 0 1 0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 0 0 1 0 1 1 1 0 1 Trinidad a Turkey Ukraine Vietnam Zimbabwe 71.2 76.3 71.7 76.3 56 1.5 10.0479 0.06 5.74141 0.8 1.09468 0.5 0.757401 14.9 0.347746 98.8349 94.1061 99.7187 93.3595 83.5827 1 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 1