I am seeking help with my statistics final. My assignments is required to be 9 pages in length, double-spaced, and in APA formatting. I am utilizing Introduction to Business Statistics (7th Edition) by Ronald M. Weiers. I am offering 17 custom credits for this assignment. I need it completed by Saturday October 22, 2016 (3:30 pm).
ASSIGNMENT MUST INCLUDE (PDF attached with the same information provided below):
INTRODUCTION - the problem scope and outline the objectives of the analysis in a clear, concise, and professional manner (1 pg)
DATA PRESENTATION: present a summary of data in an accurate and professional manner, and provide accurate interpretation of the data. Must provide an Excel table showing summary statistics of selected variables in your regression model and provide a brief description of the data. (1 pg)
MODEL SPECIFICATION & DEVELOPMENT: Must specify the appropriate linear regression model(s) in an with accuracy. Provide accurate equations for selected linear regression model(s) with a detailed description of the notation of each variable. If 2 or more regression models are estimated, provide the detail justifications for them (2 pgs)
INTERPRETATION OF RESULTS: Must provide a clear, concise, consistent and accurate summary of results from the linear regression model(s). Discuss the statistical significance of each variable, and justify the sign of each variable. Also, discuss the meaning of the slope for each variable. The interpretations must be understandable to the general public. (2.5 pages)
POLICY RECOMMENDATIONS AND CONCLUSIONS: Must address policy recommendations and/or implications in the business world in a professional manner. In other words, students must provide a clear recommendation and plan of action that government agency or property developers must take in their future decision making process, based on the results from linear regression model(s). (2.5 pgs)
Case study must cover the following issues at the minimum:
1. What are the research questions you want to investigate using this dataset?
2. Based on a multiple linear regression model, which variables are significant, and which variables are not? Did the signs of each variable come out as expected?
3. What does the results from the linear regression model show about the economic value of access to recreational lakes? Does water quality have a significant impact on house prices?
4. Are structural variables statistically significant and their signs come out as expected?
5. How would you explain the impact of population density on housing price?
6. Based on the results, what would you suggest property developers, house buyers, or local government decision makers should do?
VARIABLE DESCRIPTIONS (For Excel Spreadsheets 1 - 5):
Price Residential Property Sales in dollars (Yr: 2003)
Land_fcv Land full cash value in dollar (reflection of the market value of your property and consists of land
Age The age of property
Time Traveling time to the nearest lake in minutes
Pop_sqml # of population/mile^2 in 2000 (measured on a Census track level)
Gr_fl_ar The area of ground floor (sq)
Patio_Floor The ratio of patio area to total area (Total area=ground floor area+patio area)
Sedi_per_lake Tons of sediment loads/lake acre in the nearest lake from each residential property
Imp_scv Improved full cash value
There are total of 2,000 data points, but I broke it down to 400 data cells per page (5 Excel pages) to successfully upload the Excel information.
In other words, I put the data points in order from 2 - 400 (1 0f 5), 401 - 800 (2 of 5), 801 - 1,200 (3 of 5), 1,201 - 1,600 (4 of 5), and 1,601 - 2,000 (5 of 5). Let me know if there are any questions.
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A regression analysis in SPSS is determined.