Course Syllabus

Course Description

The purpose of this course is to provide students of public administration with statistical tools necessary to be better producers and consumers of various kinds of data and to enhance decision-making capabilities in a public management context. Students will learn, apply and critique statistical approaches to real-world situations through practical application of statistical concepts.

Course Learning Outcomes

This course is designed to promote core competencies of the MPA program and to provide students with specific skills in statistical analysis. Students who successfully complete this course will have made significant personal advances in the ability to:

• Assess and adapt to new information and changing environments
• Write persuasively with polish and professionalism
• Use common analytical tools effectively
• Convey technical ideas to all audiences, both orally and in writing
• Communicate process and results to all stakeholders
• Structure problems
• Gather, evaluate and focus information
• Critique the application of analytical tools
• Understand the substantive implications of quantitative analysis
• Work independently to accomplish new, difficult, and/or challenging tasks
• Manage time effectively

The Specific quantitative tools and concepts introduced in this course include:

• Elements of causal relationships
• Descriptive statistics (measures of central tendency, dispersion, proportions, frequency)
• Inferential statistics (confidence intervals)
• Use of z-scores
• Hypothesis testing
• Testing difference of means and proportions
• Regression analysis (including simple, multiple, logistic, and ordinal logistic analysis)
• Basic data management
• Use of statistical software

Reading Materials

Required: Berman, Evan. 2007. Essential Statistics for Public Managers and Policy Analysts, 3^{rd edition}. Washington, DC: CQ Press.

Optional: Berman, Evan. 2007. Exercising Essential Statistics, 3rd edition. Washington, DC: CQ Press.

Other readings will be assigned and posted on Canvas per the syllabus and course calendar.

Work Project

A significant component of this course is the completion of a statistics project on behalf of your workplace or another community partner. Students should come to class prepared with data on the first day of class. This data should be real and relevant to actual questions relevant to public administration.

Classroom Procedures

Before class:
Students are expected to complete and report reading assignments and report reading scores prior to class. Application work from the previous week is also due prior to the start of class. No points will be given for late readings unless prior arrangements have been made with the instructor. Late application work will be accepted but may not receive feedback.

Review & questions:
Students are invited to bring questions from previous weeks’ material and/or the assigned readings for discussion during the first portion of class. Students are encouraged to make note of their questions as they are encountered from reading or application during the week prior to class. Substantive questions posed during this portion of class will be rewarded with participation points.

Lecture & discussion:
Students are invited to be actively engaged in the lecture and demonstrations that take place during the lecture and discussion portion of the class. This is when new material will be introduced, including some material not available in the textbook. Full attention is expected during lecture. The instructor will make every effort to make lecture notes available to students so that minimal note-taking is necessary.

Technology & practice problems:
Students are invited to work independently and/or collaboratively to practice material from lecture using the practice data provided. This will help students to verify that they have the practical knowledge necessary for application to their own independent projects. The assigned practice assignments are not due to the instructor. Students who master the material before others are expected to actively engage as teachers during this time period to both solidify their own understanding of the concepts and to aid others in understanding. When students feel confident that they and their peers have mastered the material and are ready to apply it, they may move on to application.

Application:
Students will apply their knowledge to data of their choosing and prepare materials for presentation and critique. An assignment sheet outlining the output expectations for each application session will be posted online. During some class periods, students will be able to complete all of their work during class time. However, this will not always be the case. Students should be diligent about wisely using their application time during class to make significant progress on their projects and to seek help for those items with which they are least comfortable. This time should be primarily individual work time, though students may ask their peers for some help, clarification, and assistance.

Common issues/questions:
Following application, many students will have questions or issues that require instructor clarification. These will be addressed for the whole group during the issues/questions portion of class. The primary purpose of this section of class is to answer critical questions that will enable students to complete any unfinished work at home during the following week.

Presentation and critique:
Students will be invited to report on their application work during the final hour of class. Not all students will have the opportunity to present their work each week, and students will have achieved varying levels of success and completion during the application time period. Presentations may occur in pairs, groups, or whole-class settings at the instructor’s discretion. The purpose of this portion of class is to allow students to present their work using the language of statistics and to receive feedback on their work and suggestions for improvement. It is also an opportunity for the other students in class to practice being savvy consumers of statistics, strengthening their critical analysis skills and deepening their understanding of how to prepare and analyze data in the most useful and compelling way possible. Students who present work during this section of class will receive participation points.

Deliverables:
Students are expected to post their final application work for each week before the class session begins (5:00 pm). Final application work and peer reviews should be posted on Canvas. Specific details of the expected deliverables for each week are posted with the application assignment materials.

Assignment Descriptions

Participation points
Student participation points will be awarded for each question, presentation, and peer review. In class, students will be called upon in order of priority based on the color-coded priority cards handed out in class. Because the available time for participation is uncertain, the instructor will count the number of questions and comments made for each student, normalize the distribution, and award points accordingly.

Application deliverables
Each week, students will submit their draft application work. These written assignments should appear as draft versions of what will ultimately appear in the final project. Students are encouraged to craft and format their work as though it were a polished and professional written report, including professional template formatting and layout design. These deliverables will be carefully reviewed and feedback should be used to improve the quality of the final project.

Final Project - Oral
The oral final project presentation will take 2-5 minutes and should reflect the summative value added by your work. The purpose of the presentation is to clearly and succinctly identify the purpose of the project, what was found, and why the results of the project should be trusted, in addition to any particular implications, action items, or concerns.

Final Project - Written
The final written project should consist of completed, polished, and perfected components that have been developed throughout the course. The final project should be accompanied by a one-page executive summary, and be professionally presented in both hard copy and soft copy. A copy of the clean data (excel format), codebook, and final report should accompany the report.

Late Assignments
Participation and reading points cannot be made up even for legitimate and/or extenuating circumstances. Any exceptions to the late policy must be received in writing from the instructor, and should be noted by the student in the notes section of the submission form on Canvas.

Late written application assignments will not receive the formative attention received by on-time assignments. Please submit your work on time.

Online Materials
In an effort toward continual improvement, the instructor will be modifying and improving documents on this site and also on other, related sites online. If you would like to keep up with these, please view the items at the following links:

YouTube videos: https://www.youtube.com/user/evawitesman

Class help queue: https://docs.google.com/spreadsheets/d/1MmjC3h9cDyMpHvYz1rRg35dnUcl6msIQp_s0STxBRAQ/edit?usp=sharing

Grading Scale

The grading scale for Spring 2017 was as follows:

94-A

89-A-

85-B+

80-B

70-B-

60-C+