methods

methods - this data - think about (relevance, scale,...

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Title Page Abstract (not to exceed 200 words) Executive summary (not to exceed two pages) Clearly stated objectives.  Significance of project and Background Information/Literature Review Approach.           Management Plan (see Section 5B below) Deliverables.  Be specific on the nature of what you will produce. Milestones.  Include dates when you initiate and complete tasks and subtasks Opportunities for links with outside advisors and professional environmental  community Budget (see Section 7 and example in Appendix VI) Budget justification References cited
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For next week ~5 pages Introduction, RQ/objectives, Literature Review and Approach
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Method section in proposal Basic steps required to answer the research question / or meet a stated design objectives Description of data and sources, how you will collect data Description of the analysis/ what you will do with data Provide justification for why this method, why
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Unformatted text preview: this data - think about (relevance, scale, accuracy, availability, cost, accessibility, effort) Describing models in a proposal • Why this model - tell the reader enough about the model that it is clear why it is being used to answer the RQ or meet stated objective • Data used to drive the model (inputs, parameters, calibration) • Assessment of model performance (directly by comparison with data; or rely on previous studies or theory) • If needed, explain how the model results will be analyzed to answer the RQ Describing literature/document review • Describe/list document sources • Detail the specific information are you looking for? (e.g. frequency that utilities include reference to climate change in their planning documents) Surveys • Population that you are surveying • Survey instrument (interviews, mail), how you will contact them • Survey Questions • Analysis of survey data...
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This note was uploaded on 08/06/2008 for the course ESM 401A taught by Professor Tague during the Spring '08 term at UCSB.

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methods - this data - think about (relevance, scale,...

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