Psychometric evaluation and experimental validation of the statistics anxiety rating scale.

The Statistics Anxiety Rating Scale (STARS) was adapted into German to examine its psychometric properties (n = 400). Two validation studies (n = 66, n = 96) were conducted to examine its criterion-related validity. The psychometric properties of the questionnaire were very similar to those previously reported for the original English version in various countries and other language versions. Confirmatory factor analysis indicated 2 second-order factors: One was more closely related to anxiety and the other was more closely related to negative attitudes toward statistics. Predictive validity of the STARS was shown both in an experimental exam-like situation in the laboratory and during a real examination situation. Taken together, the findings indicate that statistics anxiety as assessed by the STARS is a useful construct that is more than just an expression of a more general disposition to anxiety.

A study of converter rating for brushless DFIG wind turbines

This paper studies the converter rating requirement of a Brushless Doubly-Fed Induction Generator for wind turbine applications by considering practical constraints such as generator torque-speed requirement, reactive power management and grid low-voltage ride-through (LVRT). Practical data have been used to obtain a realistic system model of a Brushless DFIG wind turbine using steady-state and dynamic models. A converter rating optimization is performed based on the given constraints. The converter current and voltage requirements are examined and the resulting inverter rating is compared to optimization algorithm results. In addition, the effects of rotor leakage inductance on LVRT performance and hence converter rating is investigated.

Autobiographical Memories for Very Negative Events: The Effects of Thinking about and Rating Memories.

In three related experiments, 250 participants rated properties of their autobiographical memory of a very negative event before and after writing about either their deepest thoughts and emotions of the event or a control topic. Levels of emotional intensity of the event, distress associated with the event, intrusive symptoms, and other phenomenological memory properties decreased over the course of the experiment, but did not differ by writing condition. We argue that the act of answering our extensive questions about a very negative event led to the decrease, thereby masking the effects of expressive writing. To show that the changes could not be explained by the mere passage of time, we replicated our findings in a fourth experiment in which all 208 participants nominated a very negative event, but only half the participants rated properties of their memory in the first session. Implications for reducing the effects of negative autobiographical memories are discussed.

Sovereign rescheduling probabilities in emerging markets: a comparison with credit rating agencies' ratings

This study estimates default probabilities of 124 emerging countries from 1981 to 2002 as a function of a set of macroeconomic and political variables. The estimated probabilities are then compared with the default rates implied by sovereign credit ratings of three major international credit rating agencies (CRAs) – Moody's Investor's Service, Standard & Poor's and Fitch Ratings. Sovereign debt default probabilities are used by investors in pricing sovereign bonds and loans as well as in determining country risk exposure. The study finds that CRAs usually underestimate the risk of sovereign debt as the sovereign credit ratings from rating agencies are usually too optimistic.

The structure of the Statistics Anxiety Rating Scale: A confirmatory factor analysis using UK psychology students

This study aimed to examine the structure of the statistics anxiety rating scale. Responses from 650 undergraduate psychology students throughout the UK were collected through an on-line study. Based on previous research three different models were specified and estimated using confirmatory factor analysis. Fit indices were used to determine if the model fitted the data and a likelihood ratio difference test was used to determine the best fitting model. The original six factor model was the best explanation of the data. All six subscales were intercorrelated and internally consistent. It was concluded that the statistics anxiety rating scale was found to measure the six subscales it was designed to assess in a UK population.

Peer Rating for Feedback in Group Projects

The National Student Survey (NSS) in the UK has since 2005 questioned final year
undergraduate students on a broad range of issues relating to their university experience.
Across disciplines and universities students have expressed least satisfaction in the areas of
assessment and feedback. In response to these results many educational practitioners have
reviewed and revised their procedures and the UK Higher Education Academy (HEA) has
produced guidelines of best practice to assist academics in improving these specific areas.
The Product Design and Development (PDD) degree at Queen’s University Belfast is
structured with an integrated curriculum with group Design Build Test (DBT) projects as the
core of each year of the undergraduate programme. Based on the CDIO syllabus and
standards the overall learning outcomes for the programme are defined and developed in a
staged manner, guided by Bloom’s taxonomy of learning domains.
Feedback in group DBT projects, especially in relation to the development of personal and
professional skills, represents a different challenge to that of individual assignment feedback.
A review of best practice was carried out to establish techniques which could be applied to
the particular context of the PDD degree without modification and also to identify areas
where a different approach would need to be applied.
A revised procedure was then developed which utilised the structure of the PDD degree to
provide a mechanism for enhanced feedback in group project work, while at the same time
increasing student development of self and peer evaluation skills. Key to this improvement
was the separation of peer ratings from assessment in the perception of the students and the
introduction of more frequent face to face feedback interviews.
This paper details the new procedures developed and additional issues which have been
raised and addressed, with reference to the published literature, during 3 years of operation.

Experimentally validated partial least squares model for dynamic line rating

This study presents a model based on partial least squares (PLS) regression for dynamic line rating (DLR). The model has been verified using data from field measurements, lab tests and outdoor experiments. Outdoor experimentation has been conducted both to verify the model predicted DLR and also to provide training data not available from field measurements, mainly heavily loaded conditions. The proposed model, unlike the direct measurement based DLR techniques, enables prediction of line rating for periods ahead of time whenever a reliable weather forecast is available. The PLS approach yields a very simple statistical model that accurately captures the physical performance of the conductor within a given environment without requiring a predetermination of parameters as required by many physical modelling techniques. Accuracy of the PLS model has been tested by predicting the conductor temperature for measurement sets other than those used for training. Being a linear model, it is straightforward to estimate the conductor ampacity for a set of predicted weather parameters. The PLS estimated ampacity has proven its accuracy through an outdoor experiment on a piece of the line conductor in real weather conditions.

Partial least squares model for dynamic rating of overhead line in wind intensive areas based on field measurements

This paper presents a statistical model for the thermal behaviour of the line model based on lab tests and field measurements. This model is based on Partial Least Squares (PLS) multi regression and is used for the Dynamic Line Rating (DLR) in a wind intensive area. DLR provides extra capacity to the line, over the traditional seasonal static rating, which makes it possible to defer the need for reinforcement the existing network or building new lines. The proposed PLS model has a number of appealing features; the model is linear, so it is straightforward to use for predicting the line rating for future periods using the available weather forecast. Unlike the available physical models, the proposed model does not require any physical parameters of the line, which avoids the inaccuracies resulting from the errors and/or variations in these parameters. The developed model is compared with physical model, the Cigre model, and has shown very good accuracy in predicting the conductor temperature as well as in determining the line rating for future time periods.