School of Information
INF = Information Science

Applied Quantitative Analysis I
Applied Quantitative Analysis is a two-course sequence in the core curriculum. AQA-I introduces students to a wide range of basic concepts and techniques relevant for policy analysis. Its primary objectives are to foster analytic thinking and to develop communication skills through quantitative models.

Analytic ability is an indispensable element of a successful policy professional. While most of the core courses in the MPA curriculum help develop this ability, this course focuses on one particular aspect: the rational approach to decision making with emphasis on mathematical and statistical methodology. The intent is not to advocate this as a policy approach or to dwell on the mechanics of specific techniques. Rather, the focus is on the abilities to conceptualize, to communicate, and to reason in precise, analytic terms. The mathematical and statistical techniques acquired in this course are beneficial side-products. Upon successful completion of this first course, students will be prepared to take any section of AQA-II, which will focus more on techniques within a specialized quantitative topic.

Ethnographic and Qualitative Research Methods
Philosophically, the course emphasizes a critical, reflexive style of ethnographic practice that acknowledges poststructuralist, Marxist, feminist, and critical race critiques of ethnography. The more theoretical readings lead to discussions of epistemology, ethics, and writing style. We also read several practical books on interviewing, participant-observation, fieldnotes, and two ethnographies that I have written. The more practical readings lead to discussions about the nuts and bolts of collecting and analyzing empirical data. Ideally, the readings help students complete a semester-long fieldwork project. If students have finished their fieldwork for a master's thesis or PhD dissertation, they can write up an aspect of that experience in lieu of the fieldwork project. The course usually draws students from a variety of departments besides anthropology, e.g. education, journalism, Asian studies, geography, sociology, psychology, advertising, art history, RTF, and American studies. It works particularly well for someone doing their thesis or doing a pilot for their dissertation.

Integrating Qualitative and Quantitative Methods
This course seeks to examine the possibilities and problems associated with the integration of qualitative and qualitative methodologies, and the importance of mixed methodological approaches for cross case comparison. It uses a Òhands onÓ approach to data collection and analysis, with assignments geared toward gaining experience with specific methodological approaches. By the end of the course you will be familiar with research ethics, the basic issues associated with qualitative and quantitative questions, probability and non-probability sampling/case selection, basic survey analysis, observational investigations, focus groups, and in-depth interviews. As our time in the course is limited, a grant proposal takes the place of a formal research paper as the final project, in order to enable participants to design complete mixed methods study with expanded time and resources.

Our goal is examining the ways in which combining methodological tools can be used to strengthen the validity or generalizability of research findings. Mixed methodological approaches are strongly encouraged. However, even those anticipating a career as an advocate of ethnography or an unapologetic analyst of secondary data can benefit from learning about the norms, methods, and principles concerning how the Òother halfÓ works. In each seminar we will cover key methodological elements of a variety of specific methods, explore examples of research utilizing the methodology, and discuss linkages and fissures between the key assumptions of and data generated by various methodologies.

Analysis of Variance
This is one of two courses in analysis of variance and the design of experiments. The analysis of variance is the main statistical tool used in the design and analysis of experiments. The first applications were to agriculture. Its applications spread to engineering experiments after World War II. We shall cover the material in the first part of Design and Analysis of Experiments by Douglas Montgomery, published by Wiley. A considerable amount of additional material will be included.

In the first half of the course I shall discuss the basic ideas of experiments with one and with two factors, interaction, blocking, components of variance, and nested designs. In the second half I shall discuss the larger experiments that are commonly used in agriculture and by engineers in gauge studies. These involve questions of fixed, random and mixed models. I shall also include split plot designs which occur in both the agriculture and engineering contexts and, if time permits, an introduction to incomplete block designs.

A moderate knowledge of multiple regression will be an advantage. I shall use the MINITAB software package to do the computations. Grades will be determined on the basis of two take-home examinations - mid term and the final that will involve the use of the computer.

Sampling
This is an initial course in the theory of statistical sampling. Most of the earlier applications were in the the field of agriculture. Lately sampling has become an important area in business and politics.

In the first part of the course I shall discuss the standard topics, such as: simple random samples from finite populations, stratified sampling, ratio and regression estimates, cluster sampling and two stage sampling.

I shall be referring to the book "Sampling: Design and Analysis" by Sharon L. Lohr, published by the Duxbury Press. In the second part of the course I discuss industrial applications to acceptance sampling, including such topics as single and multiple sampling plans, average outgoing quality, and sequential sampling. I may also include some lectures on cumulative sum control charts.

I shall be using the MINITAB software package. Many of the calculations can be done on a spread sheet such as Excel. My present plan is that grades will be determined on the basis of two take-home examinations - mid term and the final - that will involve the use of the computer.