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ICT110 Introduction to Data Science Task 2 Semester 1, 2018 ICT110 Introduction to Data Science Assignment 2 Page 2 of 7 Assessment and Submission Details Marks: 30% of the Total Assessment for the Course Due Date: 11:59pm Friday, Week 12 Submit your assignment to Blackboard Task 2. Please follow the submission instructions on Blackboard. The assignment will be marked out of a total of 100 marks and forms 30% of the total assessment for the course. ALL assignments will be checked for plagiarism by SafeAssign system provided by Blackboard automatically. Refer to your Course Outline or the Course Web Site for a copy of the “Student Misconduct, Plagiarism and Collusion” guidelines. Assignment submission extensions will only be made using the official Faculty of Arts, Business and Law Guidelines. Requests for an extension to an assignment MUST be made to the course coordinator prior to the date of submission and requests made on the day of submission or after the submission date will only be considered in exceptional circumstances. ICT110 Introduction to Data Science Assignment 2 Page 3 of 7 Background A research team planned to study the heath development of the world in the past 15 years. The team retrieved the dataset from World Bank (http://databank.worldbank.org) about Health and Population Statistics between 2001 and 2015. The dataset contains the following attributes: • Birth rate, crude (per 1,000 people) • Fertility rate, total (births per woman) • Adolescent fertility rate (births per 1,000 women ages 15-19) • Death rate, crude (per 1,000 people) • Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions (% of total) • Cause of death, by injury (% of total) • Cause of death, by non-communicable diseases (% of total) • Mortality caused by road traffic injury (per 100,000 people) • Health expenditure per capita (current US$) • GNI per capita, Atlas method (current US$) • Health expenditure, private (% of GDP) • Health expenditure, public (% of GDP) • Health expenditure, total (% of GDP) • Maternal mortality ratio (national estimate, per 100,000 live births) • Immunization, BCG (% of one-year-old children) • Life expectancy at birth, male (years) • Life expectancy at birth, female (years) • Life expectancy at birth, total (years) • School enrollment, primary (% gross) • School enrollment, secondary (% gross) • School enrollment, tertiary (% gross) • School enrollment, tertiary, female (% gross) • Total alcohol consumption per capita (liters of pure alcohol, projected estimates, 15+ years of age) • Unemployment, female (% of female labor force) (modeled ILO estimate) • Unemployment, male (% of male labor force) (modeled ILO estimate) • Unemployment, total (% of total labor force) (modeled ILO estimate) More details about the data attributes and data content can be found in the attached documents. Assignment Task You are a member of the team, and need to perform data analysis on countries in the region of East Asia & Pacific. The team has not set any specific goal for the analysis. Therefore, you have the freedom to explore the data, and dig out anything you feel interesting or significant. http://databank.worldbank.org/ ICT110 Introduction to Data Science Assignment 2 Page 4 of 7 You have been requested to prepare a data analysis report about your work and explain your findings. The potential audiences include other researchers, business representatives, and government agencies. They may have limited ICT or mathematical knowledge. To prepare the report, please follow the following outline: 1. Introduction Provide an introduction to the problem. Include background material as appropriate: who cares about this problem, what impact it has, where does the data come from. 2. Data Setup Describe how to load the data, and the libraries needed. Provide an overview of the data about its dimensions and structures. 3. Exploratory Data Analysis Perform 3 one-variable analysis. Plot at least one graph for each variable. Explain why the selected graph is appropriate. Perform 2 two-variable analysis. Plot at least one graph for each variable. Explain why the selected graph is appropriate The analysis can be performed on all years and all countries, or on a subset of your interest. 4. Advanced Analysis 4.1 Clustering Briefly explain the concept of clustering and k-means. Try to do a clustering analysis to group countries according to some selected attributes. 4.2 Linear Regression Briefly explain the concept of linear regression. Try to do 2 linear regression analysis. Plot the learned models. The analysis can be performed on all years and all countries, or on a subset of your interest. 5. Conclusion 6. Reflections In this part, discuss any difficulties you had performing the analysis and how you solved those difficulties. Reflect on how the analysis process went for you, what you learnt, and what you might do differently next time. For the data analysis, you need to provide both R code, and the explanation to the code and the result. For the section 2 – 4, please represent each R code snippet in a box with some comments. For example: # Draw a boxplot on the attribute “Income” boxplot(MyData$income) The following guidelines will be used in marking each section of the assignment: surajrimal Sticky Note ask the question which country has the high birth rate and other 2 and make the bar graph and describe surajrimal Sticky Note 1 qnd 2 anayalysis ICT110 Introduction to Data Science Assignment 2 Page 5 of 7 100% 90% 75% 65% 50% 25% 0 Outstanding: High Distinction: Distinction: Credit: Pass: Fail: Not Submitted: An outstanding attempt – well formatted and professionally presented piece of work. An excellent piece of work that meets all the specified criteria with very minor omissions or mistakes More than competently meets the criteria specified with only minor mistakes or omissions. Competently meets the criteria as specified with few minor mistakes or omissions. Satisfactorily meets the criteria. Did not sufficiently meet the criteria to pass. No attempt made or different from what is acceptable Report Format Your report should be no less than 1,200 words and it would be best to be no longer than 2,000 words long. All comments and graph titles are counted. The report MUST be formatted using the following guidelines: • Paragraph text – 12 point Calibri single line spacing • Headings – Arial in an appropriate type size • Margins – 2.5cm on all margins • Header – Report title • Footer – page number (including the word “Page”) • Page numbering – roman numerals (i, ii, iii, iv) up to and including the Table of Contents, restart numbering using conventional numerals (1, 2, 3, 4) from the first page after the Table of Contents. • Title Page – Must not contain headers or footers. Include your name as the report’s author but DO NOT include any reference to your student ID, course code or course name. • The report is to be created as a single Microsoft Word document. No other format is acceptable and doing so will result in the deduction of marks. For advise on report writing, the following book provides good advices: Summers, J. & Smith, B., 2014, Communication Skills Handbook, 4th Ed, Wiley, Australia. Referencing 2 references for the explanation of Clustering and 2 for linear regression are required. These references should follow the Harvard method of referencing. Note that ALL references should be from journal articles, conference papers, technical papers or a recognized expert in the field. DO NOT use Wikipedia as a reference. The use of unqualified references will result in the deduction of marks. Submission The completed assignment is to be submitted to Blackboard Task 2 by the due date of 11:59pm Friday, Week 12. ICT110 Introduction to Data Science Assignment 2 Page 6 of 7 The assignment will be assessed according to the marking sheet which is shown in the last page. Late submission will be penalised according to the policy in the course outline. Please note Saturday and Sunday are included in the count of days late. Assignment Return and Release of Grades Assignment grades will be available on the course website in two weeks after the submission. An electronic assignment marking sheet will be available at this time. Where an assignment is undergoing investigation for alleged plagiarism or collusion the grade for the assignment and the assignment will be withheld until the investigation has concluded. Assignment Guidelines This assignment will take a number of weeks to complete and will require a good understanding of data science and management for successful completion. It is imperative that students take heed of the following points in relation to doing this assignment: 1. Ensure that you clearly understand the requirements for the assignment – what has to be done and what are the deliverables. 2. If you do not understand any of the assignment requirements – Please ASK the course coordinator or your tutor. 3. Each time you work on any aspect of the assignment reread the assignment requirements to ensure that what is required is clearly understood. ICT110 Introduction to Data Science