## Type of Work

Article (530) Book (0) Theses (38) Multimedia (2)

## Peer Review

Peer-reviewed only (507)

## Supplemental Material

Video (2) Audio (0) Images (0) Zip (2) Other files (9)

## Publication Year

## Campus

UC Berkeley (60) UC Davis (44) UC Irvine (110) UCLA (98) UC Merced (35) UC Riverside (21) UC San Diego (43) UCSF (43) UC Santa Barbara (22) UC Santa Cruz (30) UC Office of the President (68) Lawrence Berkeley National Laboratory (184) UC Agriculture & Natural Resources (1)

## Department

Research Grants Program Office (RGPO) (62) University of California Research Initiatives (UCRI) (1) Multicampus Research Programs and Initiatives (MRPI); a funding opportunity through UC Research Initiatives (UCRI) (1)

Department of Earth System Science (14) Department of Emergency Medicine (UCI) (9) Department of Statistics, UCLA (9) Center for the Teaching of Statistics (1)

## Journal

Proceedings of the Annual Meeting of the Cognitive Science Society (31) Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health (5) Clinical Practice and Cases in Emergency Medicine (4) Adaptive Optics for Extremely Large Telescopes 4 – Conference Proceedings (3) Dermatology Online Journal (3) Frontiers of Biogeography (2)

## Discipline

Social and Behavioral Sciences (33) Physical Sciences and Mathematics (15) Medicine and Health Sciences (8) Life Sciences (7) Engineering (6) Education (2) Law (1)

## Reuse License

BY - Attribution required (60) BY-NC-ND - Attribution; NonCommercial use; No derivatives (6) BY-NC - Attribution; NonCommercial use only (3) BY-NC-SA - Attribution; NonCommercial use; Derivatives use same license (2)

## Scholarly Works (570 results)

In this paper we present an application of statistics using real stock market data. Most, if not all, students have some familiarity with the stock market (or at least they have heard about it) and therefore can understand the problem easily. It is the real data analysis that students find interesting. Here we explore the building of efficient portfolios through optimization using examples of two and three stocks, and how covariance and correlation can help the investor to diversify his or her risk. We discuss why diversification works, but also the problems that arise in portfolio management. Stock market data can be incorporated at any level of statistics, from lower division, to upper division, to graduate courses of Mathematics and Statistics. From our experience, students find this topic very interesting and often they want to enroll in other courses related to this area.

In this paper we present an application of statistics using real stock market data. Most, if not all, students have some familiarity with the stock market (or at least they have heard about it) and therefore can understand the problem easily. It is the real data analysis that students find interesting. Here we explore the building of efficient portfolios through optimization using examples of two and three stocks, and how covariance and correlation can help the investor to diversify his or her risk. We discuss why diversification works, but also the problems that arise in portfolio management. Stock market data can be incorporated at any level of statistics, from lower division, to upper division, to graduate courses of Mathematics and Statistics. From our experience, students find this topic very interesting and often they want to enroll in other courses related to this area.

This paper proposes a new analysis of the Classical Tibetan case system. After presenting the traditional as well as modern linguistics view on cases, I introduce a new analysis of the Classical Tibetan case system in ten cases: absolutive, agentive, genitive, dative, purposive, locative, ablative, elative, associative and comparative. The present description of morphology, grammatical semantics and syntax of the cases is based on four fundamental properties of the Classical Tibetan casemarkers, namely: cliticity, multifunctionality, transcategoriality and optionality. The originality of this literary case system lies in the multifunctional, transcategorial and optional nature of the casemarkers, which largely contributes to the great syntactic complexity of this old literary language of the Tibeto-Burman family.

In this paper our goal is to explain the distribution of the sample coefficient of determination in the simple regression case. We do this by using its rela- tionship to the noncentral F distribution. But first we introduce a new term, the true coefficient of determination. In a simulation study it is feasible to know the true coefficient of determination because the variance of the error term is known. The usefulness of the true coefficient of determination is in the built of relationships with predetermined strength. It answers the question: How much error should we add? The answer depends on how strong we want the association in the simple regression model to be. Once we determine this we can compute the noncentrality parameter and explain the distribution of the sample coefficient of determination. It is a simple way of explaining the distribution of the sample coefficient of determination and it is interesting at least from the educational point of view.