Quiz #07 - Linear Regression with Spatial Data

This quiz is based on all the reading assignments that you completed this week. You have 60 minutes to complete the quiz. Before you take it, you should review this week's reading assignments with the following issues in mind:

• Bennett, L., & Vale, F. (2023). Spatial statistics illustrated. Esri Press. ISBN-13:  978-1589485709 - Read Chapters 1, 2 and 6 as assigned in the Overview of Module #09 - Linear Regression with Spatial Data. As you read the text, focus on learning the answers to these questions:
  • What are the different ways of defining a geographic "neighborhood" around a focal feature for conducting spatial analyses?
  • How do the frequency (i.e., count) of features around a focal feature vary as a function of a normal distribution?
  • How do you describe varying degrees of "goodness of fit" when evaluating linear regression models?
  • How would you test for randomness of residuals when evaluating the goodness of fit of a linear regression model? 
• Regression Analysis Online Help Articles - Read the ArcGIS Pro online help articles that provide an introduction to linear regression for spatial data.  As you read the help articles, focus on learning the answers to these questions:
  • What is the definition of the independent (or explanatory) variables and the dependent variable?
  • What is the relationship between the independent and dependent variables for a positive correlation? For a negative correlation?
  • How do you use the R² value to evaluate the strength of a linear correlation? 
  • What are the key differences between Ordinary Least Squares (OLS) linear regression and Geographically Weighted Regression (GWR)?
  • When using GWR, what types of data would be associated with the Gaussian, Logistic or Poisson model types?
• Zhou, N., Hubacek, K., & Roberts, M. (2015). Analysis of spatial patterns of urban growth across South Asia using DMSP-OLS nighttime lights data. Applied Geography, 63, 292-303.
  • What data did the authors use as a proxy for measuring the extent and change in urban development in South Asia?
  • What type of satellite did the authors use to collect their data? What was the name of the instrument on the satellites that collected their data?
  • What was the range of the Digital Number values that indicated night-time brightness from the ground?
  • The authors performed a linear correlation between the log (ln) of DN values and Gross Domestic Product (GDP). What did they find? What did that mean for estimating GDP? 
  • What was the meaning of the lack of correlation (R² = 0.0187) between population growth rate and night-time lighting growth rate in Figure 7? 
• Zhang, H., Liu, Y., Chen, F., Mi, B., Zeng, L., & Pei, L. (2021). The effect of sociodemographic factors on COVID-19 incidence of 342 cities in China: a geographically weighted regression model analysis. BMC Infectious Diseases, 21(1), 1-8. 
  • What four explanatory (independent) variables did the author's use to predict the incidence of COVID-19 measured as confirmed cases per 1 million people?
  • According to Table 3, which of the original four independent variables was found to be statistically significant to explaining the COVID-19 cases in China?
  • According to Table 4, which of the independent variables was positively correlated with COVID-19 cases? Negatively correlated?