Advanced Business Statistics

Advanced Business Statistics Order Description MG315 Project Paper Outline Font Size: 12 Times New Roman Recommendation writing style: APA 1. Table of Contents 2. Chapter 1. INTRODUCTION Overview Purpose of this Report Assumptions of this Report Definitions of Terms Problem Statement Data Collection 3. Chapter 2. MODEL DEVELOPMENT Overview Model Overview Model Formulation Data Analysis Multicollinearity Autocorrelation Model Selection 4. Chapter 3. CONCLUSION Summary Recommendations REFERENCES Appendix A. Raw Data Set Appendix B. Organized Data Set (In excel) List of Tables List of Figures Project Details EXAMPLE BELOW Overview: Give background of the organization as it relates to the situation that led to the problem you are trying to solve. Purpose of this Report: Talk about the purpose and as it relates to your evaluation of the variables being used. Talk about how your analysis or tool (model) will help now and future. Assumption of this Report: Talk about if any previous work was done in this area utilizing regression, what is the reason for the problem or cause, etc. Definition of Terms: All variables, measures of central tendency, empirical rule are some examples of terms that will need to be defined. Use source reference when defining. Problem Statement: Concise statement of the problem. Use the example from the posted discussion Data Collection: Talk about your research into looking for your data. How did you find it? Additionally, talk about your source and if you feel that it is replicable or not. These are examples of discussion. Model Overview: Discuss the dependent variable as a function of the independent variables while defining them in words and use of short hand variable representation. Further, discuss the source (where do they keep the data) and the number of observation in the raw data verse the number of observations chose to use and why. Data Analysis: Talk about the final (best fit) model that you chose in terms of the descriptive statistics. Talk about the variation in the dependent variable in terms of real numbers. If you are dealing with cost or price, give a description of the model in real world terms. Discuss the variation of the dependent variable (Coefficient of Variation) and how it varies and the relationship to the independent variables and their variation. Each graph and statistics charts listed should be discussed (scatter plot, histogram, descriptive statistics, etc.) Multicollinearity: Discuss what multicollinearity is and what you did to analyze whether you have any. It is best to refer to a chart with the results of your analysis. Autocorrelation: Discuss what autocorrelation is and what you did to analyze whether you have any and what conclusions can be drawn from your results. It is best to refer to a chart or print out of the results of your analysis. Have a chart that displays the result criteria for autocorrelation. Model Selection: Include your topic and feasibility here. Additionally, write a paragraph discussing the model that you selected. You can discuss autocorrelation whether it supports your model or if it does not or inconclusive; and your recommendation for use of the model. Finally, list your best fit model with coefficients and variables. Summary: Restate your purpose paraphrased, discus the positive use of your model, and discuss the results and how it can assist in future concerns/issues. Recommendation: Discuss your recommendations in terms of what the original problem is and what you learned regarding your model, variation in the variables and how it relates to reality. Include a recommendation on improving the model (e.g., maybe you want to look at other independent variables, more observations, cross section vs time-series, etc.). References: List all references (books, websites, papers, other sources, etc.). Appendix: List a readable copy of both raw and organized data The outline above is just a guideline for minimum discussion. You may be driven to discuss more based on your problem and analysis of results. This project is out of a total of 100 points (25 percent of your total class grade). Each section theoretically would be worth 6.5 plus points each. However, some sections are worth more than others such as model overview or autocorrelation (including charts, graphs, etc.). **At minimum, your project must include all charts and graphs listed in quiz 3. Additionally, each chart and graph will be labeled and accompanied with a paragraph describing each chart and graph. Data was pulled from REDFIN real estate website, which pulled houses sold in the last 90 days in the Oceanside, CA Zip code of 92054. Dependent variable is price sold, independent variables are bed, bath, and square feet. Problem Statement: To better understand the volatile housing market within the Oceanside Coastal properties near the beach for potential buyers in the 92054 Zip Code, it is necessary to analyze the sales of homes within that area over the last 90 days. Analyzation of the data will utilize total cost of home sold, number of beds, baths, and total square footage. Analyzing these three variables (number of beds, baths, and total square footage) can provide a potential buyer a general idea of how these three variables play a key role to the driving factor of the total cost of the property. Having a understanding of the key data of variables associated with rooms, bathrooms, and square footage, will assist future potential buyers to better understand the current and market enabling them to formulate a decision to purchase at fair market value for home near the beach.