This is a Regression modeling assignment which entails real-world problem case study. For Chapter 11, case study 11.1, you will need to download the file C11_01.xlsx from the textbook companion
Regression modeling assignment-real-world problem case study
Regression modeling is a foundational skill for those conducting secondary data analysis, much like you will encounter in the completion of the Doctor of Healthcare Administration (DHA) program. Additionally, regression modeling assists in finding connections among multiple variables and one dependent variable. Consider, for example, a healthcare administrator who may asked to develop or interpret models of patient satisfaction based on other quantitative or dichotomous variables. So, for this Assignment, review the resources for this week. Then, review your course text, and complete Case Study 11.2 on page 536. The case study is based on a real-world problem.
Regression modeling assignment-real-world problem case study
(ATTACHED) For Chapter 11, case study 11.1, you will need to download the file C11_01.xlsx from the textbook companion (ATTACHED) The Assignment: (3–5 pages) Complete Case Study 11.2, “Heating Oil at Dupree Fuel Company” on page 536 of your course text using SPSS. OLS regression models widely used in quantitative analyses. However, for the geographer they can be problematic because, among a range of assumptions, they are required to be independent of the residuals.Also, it has been observed that dependencies often exist in spatial data which lead to a violation of one or more of the assumptions of the OLS model – typically, we find that the residuals are spatially autocorrelated. Besides, Spatial regression models extend OLS models in an attempt to deal with spatial autocorrelation.
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