Research proposal example - sparklabnyc/resources GitHub Wiki

The following is an example provided by the lab based on a successful goal planning. This model is based on Allison Stewart's Spring 2024 research rotation. Below you will find the full document and text blurbs to explain the document

Spring 2024 Rotation Goals and Objectives

Allison Stewart

Research Rotation Goals

During my Spring 2024 research rotation under the mentorship of Dr. Robbie Parks, I aim to accomplish the following:

1. Engage in a comprehensive research progress, including cleaning and managing data from the HINTS survey and Climate Vulnerability Index, conducting statistical and spatial analysis, presenting results to the lab group and/or EHS seminar, and initiate the drafting of a manuscript.
2. Improve my R programming skills: become more comfortable in writing clean and efficient code and expand my knowledge of statistical and spatial analysis methods in R. I plan to learn how to conduct spatial analysis in R through coursework and outside learning.
3. Refine my research focus: Narrow down my interests in both content areas and methods. This will involve developing a plan for a summer research rotation and generating ideas for my future dissertation.

Research Objective and Data Analysis Plan

Objective: Explore associations between perceived health risk of climate change and climate vulnerability in the U.S. Data Analysis

1. Data cleaning: address missing values and inconsistencies, convert variables into appropriate formats
2. Merge data: HINTS survey data and U.S. Climate Vulnerability Index
3. Determine unit of analysis: either at the county level with FIPS county codes or by converting zip codes to ZCTAs
4. Exploratory data analysis to understand distributions of perceived health risk of climate change and sociodemographic variables by location
5. Bivariate local indicators of association (LISA) cluster analysis to identify patterns and associations between perceived health risk of climate change and climate vulnerability
6. Two-sided t-tests to evaluate whether the sociodemographic characteristics of high perceived risk-high vulnerability county clusters differ statistically from other clusters
7. Spatial visualization: create maps to visually represent identified clusters and associations

Commentary

The goals planning example clearly states the research question and provides the procedure that the student will use in the research project.

During my Spring 2024 research rotation under the mentorship of Dr. Robbie Parks, I aim to accomplish the following: 
1) Engage in a comprehensive research progress, including cleaning and managing data from the HINTS survey and Climate Vulnerability Index, conducting statistical and spatial analysis, presenting results to the lab group and/or EHS seminar, and initiate the drafting of a manuscript. 
2) Improve my R programming skills: become more comfortable in writing clean and efficient code and expand my knowledge of statistical and spatial analysis methods in R. I plan to learn how to conduct spatial analysis in R through coursework and outside learning.  
3) Refine my research focus: Narrow down my interests in both content areas and methods. This will involve developing a plan for a summer research rotation and generating ideas for my future dissertation.  

This section should outline 3 clearly defined developmentally oriented goals. Each goal should reflect what you want to achieve under the mentorship. Think of these as goals to complete in the period. Fill it out with information such as what you will do in the project, what you want to learn, and what you want to figure out. Mention the project and datasets you will work with, be specific but flexible, think ahead, and plan long-term.

**Research Objective and Data Analysis Plan** 

Objective: Explore associations between perceived health risk of climate change and climate vulnerability in the U.S. 
Data Analysis 
1.	Data cleaning: address missing values and inconsistencies, convert variables into appropriate formats
2.	Merge data: HINTS survey data and U.S. Climate Vulnerability Index 
3.	Determine unit of analysis: either at the county level with FIPS county codes or by converting zip codes to ZCTAs
4.	Exploratory data analysis to understand distributions of perceived health risk of climate change and sociodemographic variables by location 
5.	Bivariate local indicators of association (LISA) cluster analysis to identify patterns and associations between perceived health risk of climate change and climate vulnerability
6.	Two-sided t-tests to evaluate whether the sociodemographic characteristics of high perceived risk-high vulnerability county clusters differ statistically from other clusters
7.	Spatial visualization: create maps to visually represent identified clusters and associations

This section states the research objective and what the student is planning to do. This document helps your mentor determine if your project is feasible and methodologically grounded. It includes the data and analytical methods that they are going to use. It is also organized logically and sequenced accordingly. This is essentially a roadmap or framework for what you are doing in the project (essentially serving as the procedural guide)