Final Project

After the first day of the course, you will choose a dataset for your final project. This can be a dataset relevant to your current research or a theoretical research question.

Your final project is an exploratory analysis of your chosen dataset. The analysis will include things such as maps and summary statistics.

Report Outline

Introduction

In this section describe what you are hoping to learn from your exploratory analysis. If applicable, describe how this exploratory analysis will impact future projects.

Data Description

In this section describe the data you are using in detail. Specifically mention

• What types of data you are using
• The data source
• What CRS you are using when analyzing the data and why
• Extent of the data
• Description of the geospatial variables
• Any limitations of your data

Visualization

In this section you must produce high quality visualizations of your data. Specifically you must

• Generate a minimum of 5 maps
• At least one map must be produced in two different softwares. These maps do not need to be identical, but they should highlight the same features.
• At least one map should show geographic features colored by the value of a geospatial variable.

Key Findings

• Describe the key findings displayed in your maps.
• Display at least 4 summary statistics
  • Ex. Table showing estimated population density of a district (estimated from a raster of population density estimates)
  • Ex. Histogram of the number of observations per sampling unit.
  • Ex. Average distance between pairs of points.

Conclusion

Summarize the key findings in your data. Describe the next steps to integrating this information into your research.

Appendix

In the appendix you will provide documentation of the steps you took to create your maps. If you use R or Python simply insert your code. If you use QGIS, write out a step-by-step plan of how you created your data file. Regardless of the software used, the information in the appendix should be sufficient for the project to be replicable.

• Must include at least: 1 raster file and 1 vector file (of any file type: wkt, shp, kml, etc)
• Must include at least 1 vector file that contains polygons
  • Ex. Country border, city border, county border, sampling area.
• Must include at least 4 geospatial data variables.
  • Ex. For every geocoded observation I know the age, gender, ethnicity, and political party.
  • Ex. For every country I know the total population, majority ethnic group, majority political party, and total spending on food.
• The data may either be obtained from an outside source OR generated by you.

Grading for this short course is pass/fail. The determination of pass/fail will be made by evaluating how well the final report meets the requirements outlined above.