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Course Criteria
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3.00 Credits
This course covers statistical model development with explicitly defined hierarchies. Such multilevel specifications allow researchers to account for different structures in the data and provide for the modeling of variation between defined groups. The course begins with simple nested linear models and proceeds on to non-nested models, multilevel models with dichotomous outcomes, and multilevel generalized linear models. In each case, a Bayesian perspective on inference and computation is featured. The focus on the course is practical steps for specifying, fitting, and checking multilevel models with much time spent on the details of computation in the R and Bugs environments. Prerequisite: ASTAT 350, 3067, 364, or equivalent.
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3.00 Credits
In factor analysis, a "factor" represents an unobservable construct hypothesized to give rise to observed variables (e.g., responses to questionnaire items). This course introduces popular factor-analytic models and methods for fitting them to data, in both exploratory and confirmatory contexts. Models for (approximately) continuous observed data are covered, as well as those for categorical observed data, including a few models and methods of item response theory. Application and interpretation are emphasized, with statistical theory introduced as needed. Use of one or more computer programs is required (prior experience with factor-analytic software is useful but not assumed). Prerequisite: ASTAT 350, 3067, 364, or equivalent.
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3.00 Credits
This course examines the significant statistical issues related to the analysis of panel data. Panel data can be generically described as containing multiple units observed at multiple points in time. Because panel data require attention to both heterogeneity and dynamics, we cover both topics individually, in summary form, before considering their interaction and developing intuitions for situations that require greater attention to one than the other. Though a host of other topics receive attention, we focus on the following issues: (1) Can individual time series be pooled and under what conditions? (2) Deterministic vs. random sources of variation arising from units or time points; and (3) What issues arise in translating techniques for panel data to censoring, truncation, and other pathologies that result in limited dependent variables? Prerequisite: ASTAT 330/513, 350/515, 363/563, 2200/5200, 3067/5067, or 364/564, the equivalent, or permission of the instructor.
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3.00 Credits
This course considers statistical techniques to evaluate social processes occurring through time. The course introduces students to time-series methods and to the applications of these methods. Coverage begins with the traditional ARIMA (Box-Jenkins) approach to time series analysis and proceed through dynamic modeling and regression approaches to recent developments such as cointegration analysis, error correction models, and vector autoregression. We learn not only how to construct these models but also how to use them in applied analysis. Heavy emphasis is given to fundamental concepts and applied work. Prerequisites for the course include a solid understanding of the fundamentals of statistical inference, regression analysis, matrix algebra, and the general linear model. By the end of the course, you should be able to: (1) use the Box-Jenkins modeling approach to prewhiten data and conduct an intervention analysis; (2) run and interpret time-series models using econometric methods such as GLS and distributed lag models; (3) analyze cointegrated data using an error correction model; and (4) use vector autoregression to analyze data and apply techniques such as impulse response and moving average response analysis to interpret results. Prerequisite: ASTAT 364 or equivalent.
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3.00 Credits
Same as JNE 179
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3.00 Credits
Same as Re St 300
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3.00 Credits
Same as JNE 301C
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3.00 Credits
Same as JNE 302
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3.00 Credits
Same as Re St 3082
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3.00 Credits
Medieval Hebrew literature includes a wide range of narratives, many of which are commonly classified as chronicles, travelogues, biographies or diaries. In this course, we explore a variety of authors and narratives from the 9th to the 17th centuries, originating from Muslim and Christian lands, the Middle East and Europe. We ask to what extent these texts mirror the personal experiences of their authors and to what extent they must be regarded as literary fictions. In addition, we discuss the question of how premodern Jewish writers reflected on history. All texts are read in English translation. Prerequisite: JNE 208F, or instructor's permission.
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