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Articles 31 - 39 of 39
Full-Text Articles in Applied Statistics
What’S Brewing? A Statistics Education Discovery Project, Marla A. Sole, Sharon L. Weinberg
What’S Brewing? A Statistics Education Discovery Project, Marla A. Sole, Sharon L. Weinberg
Publications and Research
We believe that students learn best, are actively engaged, and are genuinely interested when working on real-world problems. This can be done by giving students the opportunity to work collaboratively on projects that investigate authentic, familiar problems. This article shares one such project that was used in an introductory statistics course. We describe the steps taken to investigate why customers are charged more for iced coffee than hot coffee, which included collecting data and using descriptive and inferential statistical analysis. Interspersed throughout the article, we describe strategies that can help teachers implement the project and scaffold material to assist students …
Stochastic Processes And Their Applications To Change Point Detection Problems, Heng Yang
Stochastic Processes And Their Applications To Change Point Detection Problems, Heng Yang
Dissertations, Theses, and Capstone Projects
This dissertation addresses the change point detection problem when either the post-change distribution has uncertainty or the post-change distribution is time inhomogeneous. In the case of post-change distribution uncertainty, attention is drawn to the construction of a family of composite stopping times. It is shown that the proposed composite stopping time has third order optimality in the detection problem with Wiener observations and also provides information to distinguish the different values of post-change drift. In the case of post-change distribution uncertainty, a computationally efficient decision rule with low-complexity based on Cumulative Sum (CUSUM) algorithm is also introduced. In the time …
Variation In Rheumatoid Hand And Wrist Surgery Among Medicare Beneficiaries: A Population-Based Cohort Study, Lin Zhong, Kevin C. Chung, Onur Baser, David A. Fox, Huseyin Yuce, Jennifer F. Waljee
Variation In Rheumatoid Hand And Wrist Surgery Among Medicare Beneficiaries: A Population-Based Cohort Study, Lin Zhong, Kevin C. Chung, Onur Baser, David A. Fox, Huseyin Yuce, Jennifer F. Waljee
Publications and Research
Objective. To examine the rate and variation in rheumatoid arthritis (RA)-related hand and wrist surgery among Medicare (elderly) beneficiaries in the United States, and to identify the patient and provider factors that influence surgical rates.
Methods. Using the 2006–2010 100% Medicare claims data of beneficiaries with RA diagnosis, we examined rates of rheumatoid hand and wrist arthroplasty, arthrodesis, and hand tendon reconstruction in the United States. We used multivariate logistic regression models to examine variation in receipt of surgery by patient and regional characteristics (density of providers, intensity of use of biologic disease-modifying antirheumatic drugs).
Results. Between 2006 and 2010, …
A Dynamic-Trend Exponential Smoothing Model, Don Miller, Dan Williams
A Dynamic-Trend Exponential Smoothing Model, Don Miller, Dan Williams
Publications and Research
Forecasters often encounter situations in which the local pattern of a time series is not expected to persist over the forecasting horizon. Since exponential smoothing models emphasize recent behavior, their forecasts may not be appropriate over longer horizons. In this paper, we develop a new model in which the local trend line projected by exponential smoothing converges asymptotically to an assumed future long-run trend line, which might be an extension of a historical long-run trend line. The rapidity of convergence is governed by a parameter. A familiar example is an economic series exhibiting persistent long-run trend with cyclic variation. This …
Hierarchical Linear Modeling In Organizational Research: Longitudinal Data Outside The Context Of Growth Modeling, Irvin Sam Schonfeld, David Rindskopf
Hierarchical Linear Modeling In Organizational Research: Longitudinal Data Outside The Context Of Growth Modeling, Irvin Sam Schonfeld, David Rindskopf
Publications and Research
Organizational researchers, including those carrying out occupational stress research, often conduct longitudinal studies. Hierarchical linear modeling (HLM; also known as multilevel modeling and random regression) can efficiently organize analyses of longitudinal data by including within- and between-person levels of analysis. A great deal of longitudinal research has been conducted in the context of growth studies in which change in the dependent variable is examined in relation to the passage of time. HLM can treat longitudinal data, including data outside the context of the growth study, as nested data, reducing the problem of censoring. Within-person equation coefficients can represent the impact …
Level Adjusted Exponential Smoothing: A Method For Judgmentally Adjusting Exponential Smoothing Models For Planned Discontinuities, Dan Williams, Don Miller
Level Adjusted Exponential Smoothing: A Method For Judgmentally Adjusting Exponential Smoothing Models For Planned Discontinuities, Dan Williams, Don Miller
Publications and Research
Forecasters often make judgmental adjustments to exponential smoothing forecasts to account for the effects of a future planned change. While this approach may produce sound initial forecasts, it can result in diminished accuracy for forecast updates. A proposed technique lets the forecaster include policy change adjustments within an exponential smoothing model. For 20 real data series representing Virginia Medicaid expenses, initial forecasts and forecast updates are developed using the proposed technique and several alternatives, and they are updated through various simulated level shifts. The proposed technique was more accurate than the alternatives in updating forecasts when a shift in level …
Performance Indices For On-Ice Hockey Statistics, William (Bill) H. Williams
Performance Indices For On-Ice Hockey Statistics, William (Bill) H. Williams
Publications and Research
No abstract provided.
A Simple Method For The Construction Of Empirical Confidence Limits For Economic Forecasts, William (Bill) H. Williams, M. L. Goodman
A Simple Method For The Construction Of Empirical Confidence Limits For Economic Forecasts, William (Bill) H. Williams, M. L. Goodman
Publications and Research
A simple method for the construction of empirical confidence intervals for time series forecasts is described. The procedure is to go through the series making a forecast from each point in time. The comparison of these forecasts with the known actual observations will yield an empirical distribution of forecasting errors. This distribution can then be used to set confidence intervals for subsequent forecasts. The technique appears to be particularly useful when the mechanism generating the series cannot be fully identified from the available data or when limits based on more standard considerations are difficult to obtain.
Analysis Of Time Usage In Bell System Business Offices, William (Bill) H. Williams, Hwei Chen
Analysis Of Time Usage In Bell System Business Offices, William (Bill) H. Williams, Hwei Chen
Publications and Research
No abstract provided.