L1022: Write-Up Instructions and Marking Scheme for the Project 2024-25

Please read this document carefully – it explains how you should write up your project report and how many points you can score for different sections. You should use this document in combination with the “Project Analysis Instructions” document.

The “Project Analysis Instructions” document contains instructions on the analysis you should perform on the data. You have received your dataset via email. The datasets are different across students, and you need to use the one you were sent.

Once you have opened your data in Excel, perform the analysis as stated in each question in the “Project Analysis Instructions” document. (You can use another software if you are more comfortable with it.) Then write up your results in a word document and copy in your tables and graphs from Excel. (In the end, you need to submit one Word or PDF document. Do NOT submit an Excel file with your calculations.)

5% of the marks will be given for the general presentation of the report. To achieve these marks, make sure your report has:

A clear coherent structure (using sub-headings where appropriate)

Clear, concise writing that is easy to understand

Numbered tables and graphs with clear headings

Coherent formatting. (There are no particular rules for the formatting; it just has to be reasonable and consistent throughout.)

The suggested general format for writing up the project and marks available for each section is as follows:

Give your project a title and begin with a short introduction summarising your project. Define your variables and identify the questions you will address using the provided data. Use academic literature to give background information on the topic. You only need to provide a handful of sources here, but make sure you cite them correctly. [10%]

Descriptive statistics (question 1): Describe the data, using summary statistics and graphs, as appropriate. Provide a well-formatted table showing descriptive statistics for all variables and discuss them in the text. Use at least four graphs to show important or interesting features of the data. Make sure your graphs are properly formatted. Provide a written interpretation of each graph. [15%]

Correlations (question 2): find the correlation coefficients, test their statistical significance, and comment on the results. Write out the full test procedure for the first hypothesis test (no need to repeat the full test procedure for the second test). Provide an interpretation of your results. [10%]

Correlations (question 3): find the correlation coefficients and interpret them. You do not need to test their statistical significance. [5%]

Test whether countries that impose legal restrictions on women’s ability to work have higher adolescent fertility rates (question 4): make sure you clearly write out all steps of the hypothesis test and interpret your results. [10%]

Simple linear regression (question 5): Show your regression results and interpret the intercept and slope coefficients. Write out the hypothesis test for statistical significance of the slope coefficient. Comment on your results. [10%]

Multiple linear regression (question 6): Show your regression results and interpret the regression coefficients. Comment on the economic and statistical significance of all the slope coefficients. (You do not need to write out the hypothesis tests here, just state the results.) [5%]

R-squared (question 7): Interpret the R-squared and make sure you clearly write out all steps of the hypothesis test and interpret your results. [10%]

Multiple linear regression (question 9): Show your regression results and interpret the regression coefficients. Comment on the economic and statistical significance of all the slope coefficients. (You do not need to write out the hypothesis tests here, just state the results.) [5%]

Comparing regression models (question 10): Explain which of the regression models fits the data best. How do you decide? And why do you think this particular model happens to work best? [5%]

Prediction (question 11): Make sure you write out the regression equation, show and interpret your result. [5%]

Conclusions. What are the overall findings of the project? How does this relate to the literature you discussed in the introduction? Are there potential policy implications? [5%]