Correlation between GDP Per Capita and Life Expectancy

You have been provided with a spreadsheet giving various statistics about the state of the nation for 50 countries. Unless otherwise specified, the data were current as of 2010 and were synthesised from a number of Internet sources. Specific details are as follows. GDP per Capita: The value of all goods and services produced in a country in a given year divided by the mid-year population. Figures are for 2010, from the International Monetary Fund. See http://en.wikipedia.org/wiki/ List_of_countries_by_GDP_(PPP)_per_capita for a link to the original data and more information. Total Population: Correct as of 2010 in most cases, but some figures are estimates. Total Area: Given in km2. It includes all land and water area within the country. Obtained from Wikipedia. Vehicles per 1000 people: Obtained from the number of registered vehicles and the population figure. Climate: Roughly divided into one of 5 types. Annual number of births (in thousands): Obtained from UNICEF Life Expectancy at Birth: Obtained from UNICEF Total adult literacy rate (%): Obtained from UNICEF Key to climate: 1 = Varied 2 = Continental – Extremes of heat and cold 3 = Temperate (No extremes of heat or cold) 4 = Tropical (hot all year) 5 = Mediterranean – warm dry summer, cool wet winter Task You will need to research the context and the variables and use the statistical enquiry cycle to carry out a statistical investigation to determine if there is a relationship between at least one pair of variables. Write a report describing the investigation. 1. Familiarise yourself with the data set provided. This will include doing research to help you understand the variables and develop a purpose for the investigation. 2. Pose an appropriate relationship question that can be answered using the variables in the data set. The variables you choose must be numerical, and the variable you use as your dependent variable must be continuous. You may choose to investigate more than one pair of variables. Select appropriate display(s) to graph your data. 3. Identify features in the data, including the Trend, Association, Strength of Relationship, Scatter, Outliers/Unusual features, and Groupings. 4. Find an appropriate model. 5. Use your model to make prediction(s). 6. Write a conclusion answering your question. 7. Support your conclusion by referring to your analysis and/or features of the visual display(s). Include a reflection on your process, which could consider other relevant variables, or evaluate the adequacy of your model(s). In creating your report or presentation, link your discussion to the context and support the statements you make by referring to the statistical evidence. The quality of your discussion and reasoning, in particular with respect to any decisions and assumptions that you make will determine your overall grade. 1. Problem: State the problem you are going to investigate. You should make it clear what the variables are that you’re investigating and what the population is that you’re making claims about 2. Plan: What are you going to do to answer this problem? Give me a list of the steps you’ll go through and how you’ll use the information to make a conclusion. 3. Data: Gather the data you need, and discuss if there are any considerations you need to make. Did you need to remove any data? Why? 4. Analysis: Draw your scatterplot Find the mean point and plot your Line of Best Fit Use technology to calculate the Regression Line Explain the meaning of the slope and y-intercept in context. TARSOG: Trend, Association, Relationship, Scatter, Outliers, Groupings 5. Conclusion: What does your analysis of your SAMPLE indicate to you about the POPULATION you are investigating? Make an interpolation and extrapolation and report your results in context. Discuss any limitations to your results/findings. Are there any further things your findings make you wonder? Are there any things you would go back and change?

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