Once downloaded project file, you will need to transfer the data into Excel (copy and paste itin rather than re-type so as to avoid mistakes) and use the commands and functions in Excel to undertakethe statistical analysis.Follow the instructions in your project document, providing full and clear answers. Interpret your answersfully, by providing complete statistical and economic interpretations.Writing up the Project ReportProject should be written up in a report style, with an introduction summarising the research questions,data and methods used. It should conclude by highlighting key results, drawing conclusions and, whereappropriate, policy implications.Further:? Use numbered headings and sub-headings.? Number all tables and graphs, and refer to them in the text, with a brief discussion of each.
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L1022: Assessed Coursework Project
The Relationship between Infant Mortality, Income and Public Expenditures in
Sri Lanka 1951 to 1981
Infant mortality rates have fallen sharply in most countries, rich and poor, over the
second half of the twentieth century. Different hypotheses have been proposed to
explain this unprecedented trend over the broad sweep of history. Income per capita
increased steadily in large parts of the world during this period. Also expenditure on
healthcare and education is now significantly higher than in the 1950s. The objective
of this project is to establish whether GDP, health and educational expenditures per
capita are determinants of the infant mortality rate in one particular country: Sri
The data below contains information on the infant mortality rate (IMR), real Gross
Domestic Product per capita in rupees (GDPPC), as well as educational and health
expenditures per capita in rupees (EDUCPC and HEXPPC) for Sri Lanka, covering
the period 1951 to 1981.
1. Describe the data, using summary statistics and graphs, as appropriate.
2. Calculate the pair-wise correlation coefficients between IMR and each of the other
variables. Test the statistical significance of each correlation coefficient.
3. Estimate a regression model of the form:
IMRt =a + ß1GDPPCt + ß2HEXPPCt +ut
where the t subscript corresponds to year t, Interpret the coefficients that you
obtain, and comment on their economic and statistical significance..
4. Interpret the R2 statistic from the regression and test whether it is statistically
5. Predict the IMR for Sri Lanka at a GDP per capita level of 750 rupees, assuming
HEXPPC is at its mean value.
6. Re-estimate the model including the EDUCPC variable and comment on any
changes to the results and goodness of fit:
IMRt =a + ß1GDPPCt + ß2HEXPPCt + ß3EDUCPCt +ut
Explain how the omission of EDUCPC in part 3 may have biased the results.
(Note: it is sufficient to discuss the changes, without explicitly showing the testing
7. What conclusions do you draw from your analysis?
Copy and paste the data into Excel and conduct all the analysis in Excel.
IMR GDPPC HEXPPC EDUCPC
= the year of observation;
= Infant Mortality Rate per 1000 live births
= Real GDP per capita in rupees
= Real Educational Expenditures per capita in rupees
= Real Health Expenditures per capita in rupees
Marking Scheme for L1022 Project
Each project document contains instructions on what to do with the data. You need to ensure
you follow those instructions. Once you have copied and pasted the data into Excel, perform
the analysis as stated in each question in your project document.
The suggested general format for writing up the project and marks available for each section
is as follows:
1. Select a project and indicate its title. Begin with a short introduction summarising
your project. Define your variables, and identify the questions you will address using
the provided data. [10%]
2. Descriptive statistics: calculate descriptive statistics and summarise the key features
of the data using suitable graphs. Provide a written interpretation. [15%]
3. Correlations: find the correlation coefficients between pairs of variables and test their
statistical significance. [10%]
4. Regression model: estimate the regression model in the project sheet and display the
results in a table. Comment on the economic and statistical significance of the
estimated coefficients. [20%]
5. Interpret the R2 and test the overall goodness of fit of the model. [10%]
6. Prediction: show your workings and interpret your predictions. [10%]
7. Re-define the model as required in the project sheet and estimate it. Comment on any
changes to the results and goodness of fit. Note: it is sufficient to discuss the changes,
without explicitly showing the testing procedure. [15%]
8. Conclusions. What are the overall findings of the project? [10%]
Remember that top marks will only be awarded to clearly presented, accurate and well
written answers. For example: tables presented without supporting explaining explanation
will not score high marks.
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