GIS 470 Statistics For Geographers Final Projects 2018

GIS 470 Statistics for Geographers FINAL PROJECTS - 2018 Introduction The final project is an opportunity to synthesize what we have learned across the entire semester. You are asked to complete a statistical analysis of primary data from start to finish, beginning with articulating a hypothesis and identifying appropriate variables and ending with a conclusion based on inferential statistical testing. Your grade on the final project will be based on the extent to which you can demonstrate mastery of the concepts we have learned in class. The exact manner in which you design your project is up to you, but the ideal project will demonstrate mastery of: · Organizing and categorizing data · Descriptive statistics · Statistical distributions · Means comparisons · Correlation and regression By primary data, we mean data that you “collect” on your own – although these data could be collected many different ways, including your own observations, analysis of imagery or text, surveys, etc. Downloading a data set from the internet and then generating new metrics from those data for your analysis may be acceptable in some cases. Logistics You may work individually or in groups of no more than four students for your final project. Each “team” must collect its own primary data, but teams can work on the same type of problem and even collect the same type of data (although, ideally, not at the exact same location/time). Groups of three or four students should designate a coordinator/manager who will be responsible for ensuring that the team works cohesively to achieve its goals. Expectations regarding the amount of work that teams complete vary by group size. As a rough guideline, teams should collect and analyze three variables per group member. Possible configurations for variable collection include: One person 2 independent variables, 1 dependent variable Two people 3-4 independent variables, 1-2 dependent variables 3-4 people 5-9 independent variables, 1-3 dependent variables To reasonably conduct most of the statistical tests we have been using, groups should aim to collect at least 20-30 observations, and at least 10-15 observations for each “category” of any independent variable. More observations are certainly welcome and will increase the quality of your analysis, but please do not spend dozens and dozens of hours collecting data. Division of labor and effort should be equal among all team members. Each team member should be fully capable of answering any question about the data collection, analysis, or interpretation thereof, and thus it is strongly recommended that all team members be involved in all parts of the project. The final project represents 35% of your semester grade. Your grade on the final project will be based on your data collection plan (5%), sound analysis of your data (10%), a written report summarizing your findings (10%), a short in-class presentation (5%), and a brief reflective statement on your own experience this semester (5%). A recommended timeline for project stages: Groups formed and research questions identified by Thursday, April 19 Data collection and analysis plan written (due) by Monday, April 23 One plan per group uploaded to Blackboard, sections 1-5 from t.o.c. below Data collection complete by Tuesday, April 24 Data analysis complete by Friday, April 27 Draft report written (due) by Wednesday, May 2 One draft report per group uploaded to Blackboard Presentation prepared (due) by Wednesday, May 2 One presentation per group (7 slides max) uploaded to Blackboard Final report written (due) by Friday, May 4 One report per group uploaded to Blackboard, plus R code Reflective statement (due) by Friday, May 4 One statement per student ( words) uploaded to Blackboard Final Reports The exact length of project reports will vary by group size. You should use as much space as you need to communicate your findings. Individual reports will probably not need to exceed 7 pages, including figures. Teams of two will probably not need to exceed 10 pages, and teams of three or four will probably not need to exceed 15 pages. Your final reports should describe what your group completed at each stage of project design, analysis, and interpretation. A recommended table of contents for the final report, which may also serve as a useful guide for completing your project, is shown below. 1. Project Title 2. Team Members 3. Research question(s) 4. Description of independent and dependent variables Type of variables Expected distribution of variables Potential unusual cases/difficulties Specific hypotheses about the relationships between the independent and dependent variables 5. Data collection and analysis plan Estimated number of observations Location(s) and schedule for sampling, sampling interval Measurement type/unit/mode (for each variable) Anticipated data collection challenges Descriptive statistics to report Statistical tests to employ sections 1-5 are due by Monday, April 23 6. Data collected (mirror section #5, after data collection is complete) Problems encountered Metadata, missing data codes, other necessary coding 7. Data analysis Descriptive statistics for each variable Graphical summaries for each variable and combinations of variables Comparison of distribution for each variable to expected distributions One sample tests for certain variables against expected values Two sample tests for certain variables based on groups Analysis of variance tests for certain variables based on 3+ groups Correlation analysis for certain variables Regression analysis for certain variables 8. Interpretation Decision to accept or reject original hypotheses Potential causal explanations for observed patterns Variables excluded from the analysis that may have been important Extent to which data collected meet necessary assumptions for certain analyses Strengths and weaknesses of study design Recommendations for future projects on related topics Broader impacts/societal implications of your findings 9. Conclusions 10. External data sources/references (if necessary) Good luck! We are looking forward to seeing your work. GIS 470 Statistics for Geographers Final Projects 2018, page 3

Paper For Above instruction

Understanding the intricacies of spatial analysis and statistical methods is essential for geographers aiming to interpret complex geographic phenomena accurately. This final project in GIS 470 provides an opportunity to apply the comprehensive knowledge acquired during the semester through a rigorous analysis of primary data. The project emphasizes the importance of designing a well-structured research plan, methodical data collection, and robust statistical testing to derive meaningful conclusions about geographic patterns or relationships.

The process begins with formulating a clear research question or hypothesis related to a spatial or geographic phenomenon. This involves identifying relevant variables—both independent and dependent—and hypothesizing about their potential relationships. For example, a student might hypothesize that proximity to urban centers influences property prices, with variables such as distance to the city center (independent) and property value (dependent). By defining these precisely, students set the foundation for their analysis.

Next, developing a detailed data collection plan ensures the quality and relevance of the primary data. This includes deciding on the number of observations needed—ideally between 20-30 for statistical reliability—and determining sampling locations, intervals, and measurement types. It is crucial that all group members understand and can answer questions about data collection methods, ensuring consistency and accuracy throughout the process.

Following data collection, the analytical phase involves descriptive statistics to summarize the data's basic features, revealing patterns, trends, and variability. Visualization tools such as histograms, boxplots, and scatterplots facilitate understanding of data distribution and relationships among variables. Inferential statistical tests, including t-tests, ANOVA, correlation, and regression analyses, help evaluate hypotheses and determine the strength and significance of relationships.

Interpreting the results involves assessing whether hypotheses are supported or rejected based on statistical evidence. This step considers potential causal explanations, confounding factors, and the robustness of the data. It is also important to acknowledge any limitations or biases encountered during the study and propose recommendations for future research on similar topics.

The final report should comprehensively document each stage of the project, from research question formulation to conclusion, aligning with the provided table of contents. Clear articulation of findings, supported by statistical outputs and graphical summaries, ensures that the study's implications are well-understood. Additionally, incorporating external data or references validates the analysis and contextualizes results within existing literature.

Overall, this project underscores the importance of systematic planning, meticulous data collection, and rigorous statistical testing to produce meaningful geographic insights. The skills developed through this assignment are foundational for conducting credible spatial research, informing policy decisions, and advancing the scientific understanding of geographic phenomena.

References

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