As we have seen, the ability to reason quantitatively is not “just another curriculum requirement”; it’s an essential aptitude for successful participation in society. The topics are necessitated by everyday experience but are certainly not trivial. These skills (not addition/multiplication or solving a series of numerical or symbolic equations, but a quantitative/data-driven approach to problem-solving in general) are integral to understanding and solving real problems in the real world. In this assignment, you will take on the role of a research assistant on a data analytic investigation of patterns and trends associated with the concept of human development across the states of the US. Your job is to analyze a pair of indicators (variables) using the methods we’ve learned in class. The values of the indicators are collected and reported by Measure of America, a project of the Social Science Research Council (http://www.measureofamerica.org/human-development/ (Links to an external site.)), in the provided Excel filePreview the documentView in a new window. You will choose the pair of variables depending on your own areas of interest; they vary from economic to educational to environmental policy measures. You will explore each variable’s individual distribution as well as the possible relationship between the two.
PRELIMINARY STAGE: Introduction, 1-2 pages. In your own words, describe the idea of human development as it is defined by Measure of America (see http://www.measureofamerica.org/human-development/ (Links to an external site.)). Then, choose two variables that you would like to study. Explain each variable in your own words and going beyond a simple definition. Do not chose variables that you do not understand. Use the following questions to guide your narrative:
What does it measure?
What are the units?
How is it obtained?
Address any patterns you expect to see across the four different regions of the United States, as they are commonly defined by policy analysts and policy makers, and why. Describe any possible relationships between the variables. State the question that you will be trying answer and your hypothesis here. Although this part is based primarily on your experience and observations, you will need to include a brief literature review with citations. Two articles contextualizing your hypothesis will suffice.
ANALYSIS STAGE ONE: Univariate Analysis, 2-2.5 pages. First, analyze each variable separately. Review the definition of the variable and the information it conveys. Do the numbers seem to agree with your understanding of the definition of the data? Perform informative univariate explorative/descriptive data analysis. Describe the distributions (visually, numerically, and verbally). Describe any patterns you see (relative to the regions of the states, population densities, political leanings, etc.). Check for outliers.
ANALYSIS STAGE TWO: Pair-wise Bivariate Analysis, 1-2 pages. Relate your pair of variables by studying the scatter plot and performing basic regression analysis. Create the scatter plot with Excel and describe the relationship between the variables using the language learned in class. Insert the line of best fit on the scatter plot, including the R-squared value. Explain the implications of your observations and analysis. Comment on any unusual observations.
FINAL STAGE: Summary and Investigation Suggestions, 1-2 pages. Look at the overall data. Now that you have some familiarity with the data, look at it broadly, and relate your findings to your original hypothesis. Make sure to include any relevant graphics. Note related questions prompted by your results, but could not be answered with your analysis. Suggest additional data, analysis, or exploration that could be used to help answer those questions.
Tips for Writing the Final Report
At each step, keep notes of your thoughts and observations. You should keep notes summarizing your observations to accompany any graphics or numerical analysis created in Excel to help yourself remember what each graph/chart shows.
As you begin to write your report, first review your notes. Select the important points, and only use your relevant observations. Group them and put them in a logical order. Decide which charts and/or tables you want to include, supporting the important points of your report. All figures should be referred to directly in the text (before they appear in your report). Base your report on these notes.
Use a popular writing style. Write on the same level of difficulty that you would if you were writing for a town newspaper science section, for readers who are intelligent, but untrained in statistics. Do NOT use a style that would only be appropriate for a professor of statistics. Make sure that any graphs or charts are easily read by the non-technical public. Do not include material or views in the article that you do not have analysis or sources to support.
The appearance of your document is important. The appearance of any document affects the judgments made of it. Spend time and effort making your document look professional; after all, you will have put a lot of work into the research and analysis, and you’ll want that to be evident.
Organization is key. Use sections in your document (e.g., introduction, discussion of the basic data, conclusions, etc.). Choose where to section and how to title your sections as you wish (creativity is good, but explanatory is essential). All figures should be labeled appropriately and directly referred to within the text before the figure appears.
Analysis (30%) Appropriate bivariate and univariate analyses performed correctly and explained accurately.
Depth (25%) Context of the variables is thoroughly explored and documented with external sources. Interpretation of analysis is thoughtful, not just a basic description of the graphs. Analysis is thoroughly performed. Conclusions and suggestions for future investigations are thoughtful.
Figures (15%) Graphs/Tables/Charts are easy to read, labeled appropriately, and referred to and discussed in the report. All figures are useful in helping the reader understand the data and/or conclusions.
Organization and Format (15%) Sectioning is used appropriately and effectively. Figures look nice and are arranged thoughtfully. Entire report is organized aesthetically. External sources are cited appropriately.
Clarity (15%) Explanations of context, analysis, figures, and conclusions are clear and concise and written for a non-technical audience. Spelling and grammar are used correctly. The writing flows well, with all figures adding to the reader’s ability to understand the analysis and interpretation.
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