write paper using multiple regression analysis to address a research question; Stock Market Returns and Weather

. Introduction/Background What is the research question and why should we care? What has already been done on this topic? o Brief summary of existing work that is most relevant to your topic with proper citations (at least three). The literary review should provide the existing state of knowledge on the topic. o Commonly used databases for journal articles include: PsycInfo (Psychology), Econ Lit (Economics), ABI/Inform Global (Business), EbscoHost (General). All are available at the library website. Otherwise, Google the key words of your topic. What do you do? In what ways is your analysis different from what has been done? o These differences do not need to be profound. But your paper should not be a step-by-step replication of someone else's analysis. What data are you using? What statistical method(s) do you use? What are the main results and takeaways from your analysis? 2. Research Method Describe the hypothesis/hypotheses you plan to test Provide the main regression equation(s) you estimate o Consider starting with a primary equation. If you also estimate slight variants of the main model, it is acceptable to simply explain the changes to the model directly in the text without writing out a new equation. Explain what the dependent and key independent variables are Discuss the expected signs of the key regression coefficients, whether non-linear relations might be present, what kind of interactions among independent variables you should look for and so on. Explain why you choose the control variables--- this is when the literary review matters! 3. Data Overview What is the unit of analysis (individuals, states, counties, products, etc.)? How many observations? Generally speaking, more degrees of freedom and hence more observations lead to better estimations. The minimum number of observations is 30. Where and when? (e.g. US counties from 1990, 2000, 2010) What is the data source? (e.g. US Population Census, US Census Bureau website) Did you assemble the data set yourself? Did you drop any observations? What rules did you use in deciding what data to drop? Include summary statistics of the main variables (means, standard deviations, correlations, etc.) in a table (required) Provide the correlation matrix of independent variables (required) Extra credits are given to additional exhibits that reveal the relationship between dependent and independent variables 4. Results and Discussion

Key results o Report regression coefficient estimates and their standard errors or P-values by column in each output table (required). You cannot copy the original output table from Excel or R o Explain adjusted 2 and F statistics Interpretation: What do we learn from the regression results? Are there other ways to interpret your results? Alternative explanations? Why did you choose your main explanation over these? Are there important limitations to your analysis? Other caveats? Any suggestions for further research?

References Include a reference list of works cited and data sources used (including web links) at the end of the text. Tables and Figures You can put tables and figures directly in the text or at the end of your paper. Make sure you explain each table and figure in the text. All tables and figures should be properly numbered with clearly explained titles and notes. The variables are clearly defined, i.e. I shouldn't have to go searching through the main text to understand what they mean.