Application 3: Introduction (project and data description)
- Due May 16, 2017 by 5pm
- Points 100
- Submitting a file upload
- Available until May 30, 2017 at 11:59pm
Complete the Introduction section of the template Download template, including all subsections describing the project and the associated data.
Select a title and theme for your report, though the title may change over time as you complete more of the project.
Examples for several of these subsections (project purpose, data description, data cleaning procedures, and data evaluation) are described below:
Project purpose
Example writeup:
Springville City is interested in Springville citizens’ overall satisfaction with city services. This analysis will therefore 1) describe citizens' general level of satisfaction with each department and with the city as a whole, and 2) determine the impact of each individual service department (police, fire, sanitation, parks, etc.) on citizens' overall satisfaction levels, controlling for demographics, type and duration of residency.
Data Description
Example writeup:
The data for this analysis is based on a survey of employees of Utah State, which was conducted in June of 2011. The unit of analysis for this study is individual employees. A list of all Utah State employee e-mail addresses was obtained from the office of human resources and used as the sampling frame for this project. We sent survey requests to 500 randomly selected employees from this list. The online survey consisted of 23 questions and took approximately 7 minutes to complete. Questions on the survey include demographic variables, work satisfaction variables, overall happiness measures, job descriptors, and a variety of information about the quality of conditions in the workplace generally. Of the 500 employees who received requests, 250 responded with complete surveys yielding a response rate of 50%.
In this analysis, we are primarily interested in work satisfaction. The work satisfaction variables were measured on a 7-point Likert scale from "strongly dissatisfied" (coded 1) to "strongly satisfied" (coded 7). There are three satisfaction questions, and each of the questions were phrased in the following manner: "On a scale of 1 (strongly dissatisfied) to 7 (strongly satisfied), how satisfied are you with [work element]?" The work elements considered are pay, benefits, work schedule, work environment, and opportunities for professional growth.
Data cleaning procedures
Example writeup:
In order to keep as many observations as possible, missing values for the variable measuring community interest in participating in community councils were replaced with values indicating lack of interest. In other words, for those who did not indicate whether or not they were interested in participating, we assumed that they were not interested. We expect this assumption to provide more conservative estimates of expected participation rates in community councils.
Following data cleaning, there were useable responses from 426 citizens in this dataset. Given that the survey was originally sent to 1000 potential respondents, this represents a 42.6 percent effective response rate.
Data evaluation
Example writeup:
The data for this study were gathered from a survey of missionaries currently serving in the MTC. A better and more comprehensive approach would be to incorporate the survey questions into the administrative data collected on the intake form when missionaries first arrive at the MTC. This would allow us to track the impacts of key program changes and compare results over time. Several of the questions (language ability, cultural competency, service orientation) were self-reported on individual 5-point Likert scale questions. These constructs would be more reliably measured and externally valid if they were assessed by trained MTC employees based on multi-question indexes developed based on the psychology literature.
Rubric
Criteria | Ratings | Pts | |
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Quality of communication for intended audience
threshold:
pts
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pts
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Appropriate use of statistical terminology
threshold:
pts
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pts
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Appropriateness of methodology
threshold:
pts
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pts
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Added value of analysis
threshold:
pts
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pts
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Total Points:
100
out of 100
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