Registered nurses entering a Nurse Prescriber programme participated in a mixed methods case study to explore the extent of their bioscience knowledge and the confidence with which that knowledge was held. Forty two Nurse Prescriber students, aged 26 – 55 years, from a range of job roles were recruited. Using questionnaires and interviews, both quantitative and qualitative data were obtained. An examination of the Nurse Prescribers’ views of pre-registration nursing demonstrated that the knowledge gained had been related to practice but had been both superficial and lacking in breadth. The bioscience in pre-registration programmes had not sufficiently prepared the participants for their roles as registered nurses. The importance of experiences gained as a registered nurse in the practice setting in the learning of bioscience was strongly emphasised. Participants reported greater learning of bioscience by informal methods such as work experience, use of books and the Internet and discussion with colleagues than from experiences in the classroom. Interviewees placed particularly strong emphasis on the importance of learning from medical colleagues. The role of post-registration programmes emerged as important in learning bioscience because it related to the job role. Post-registration courses also emerged as significant in giving confidence to the registered nurse. Confidence increased not just in terms of the knowledge held, but also in terms of nurses’ ability to communicate with patients, relatives, and doctors, their ability to understand nursing skills, and their willingness to admit when something was not known.

The use of the p-value in determination of statistical significance—and by extension in decision making—is widely taught and frequently used.  It is not, however, without limitations, and its use as a primary marker of a worthwhile conclusion has recently come under increased scrutiny.  This paper attempts to explain some lesser-known properties of the p-value, including its distribution under the null and alternative hypotheses, and to clearly present its limitations and some straightforward alternatives.

The thesis examines isolation and caritas, or charity, in The Confidence-Man as polar themes which express, respectively, withdrawal from and suspicion of the human community and integration within and appreciation for that community. Isolation is considered a negative theme; caritas, an affirmative theme.

Master of Science / Department of Statistics / Paul Nelson / Effect size is a concept that was developed to bridge the gap between practical and statistical significance. In the context of completely randomized one way designs, the setting considered here, inference for effect size has only been developed under normality. This report is a simulation study investigating the robustness of nominal 0.95 confidence intervals for effect size with respect to departures from normality in terms of their coverage rates and lengths. In addition to the normal distribution, data are generated from four non-normal distributions: logistic, double exponential, extreme value, and uniform. The report discovers that the coverage rates of the logistic, double exponential, and extreme value distributions drop as effect size increases, while, as expected, the coverage rate of the normal distribution remains very steady at 0.95. In an interesting turn of events, the uniform distribution produced higher than 0.95 coverage rates, which increased with effect size. Overall, in the scope of the settings considered, normal theory confidence intervals for effect size are robust for small effect size and not robust for large effect size. Since the magnitude of effect size is typically not known, researchers are advised to investigate the assumption of normality before constructing normal theory confidence intervals for effect size.

Volatility plays an important role in option pricing and risk management. It is crucial that volatility is modelled as accurately as possible in order to forecast with confidence. The challenge is in the selection of the ‘best’ model with so many available models and selection criteria. The Model Confidence Set (MCS) solves this problem by choosing a group of models that are equally good. A set of GARCH models were estimated for several JSE indices and the MCS was used to trim the group of models to a subset of equally superior models. Using the Mean Squared Error to evaluate the relative performance of the MCS, GARCH (1,1) and Random Walk, it was found that the MCS, with an equally weighted combination of models, performed better than the GARCH (1,1) and Random Walk for instances where volatility in the returns data was high. For instances of low volatility in the returns, the GARCH (1,1) had superior 5-day forecasts but the MCS had better performance for 10-days and greater. The EGARCH (2,1) volatility model was selected by the MCS for 5 out of the 6 indices as the most superior model. The Random Walk was shown to have better long term forecasting performance.

Ceasing tobacco use benefits smokers regardless of age; therefore, it is essential for health care providers to consistently identify smokers and offer evidence-based cessation treatments to those wanting to stop smoking as a proactive approach towards tobacco abstinence. The purpose of this doctoral project, which was underpinned by the knowledge-to-action framework, was to educate nurse practitioners about evidence-based tobacco cessation interventions and assess the impact of the education on their knowledge base, skills, and self-confidence in implementing tobacco-cessation protocols. Participants (n = 14) completed a knowledge-based questionnaire and the Skills and Confidence for Smoking Cessation Tool before and after an education intervention based on the Rx for Change program. Paired sample t-tests were completed to analyze the pretest and posttest results. The results indicated a statistically significant increase (p < .05) in perceived knowledge, skills, and confidence among nurse practitioners related to tobacco cessation education. These findings support the use of tobacco cessation education for nurse practitioners to improve this aspect of care and provide patients with effective interventions to improve quit rates. The impact of this project on positive social change includes fostering a healthier lifestyle for tobacco users that extends to family and community.

Drucker (1994) pointed out that the management of non-profit organization is not driven by profit-making motives, but lead by a mission. Support for the organization is derived from a mission that responds to social needs. In today faced liberal and multifaceted society, the development of non-profit organizations will face competition like ordinary business enterprises. It is an important issue to the non-profit organization of how to gain confidence from the general public. This is also what motivated this study. Therefore, the objectives of the study are: (1) to understand the perspectives of social welfare non-profit organizations on capacity building; (2) to understand how social welfare non-profit organizations build organizational capacity; and (3) to investigate the relationships between capacity building, organizational effectiveness and public confidence in social welfare non-profit organizations. The subject of the study includes non-profit organizations in the city and county of Kaohsiung and Ping-Tung that provide social welfare related services. A mail questionnaire was distributed and the results analyzed by SPSS statistical software. The capacity building and competency model developed by Paul C. Light (2004) was used in explaining the relationship between capacity building and organizational effectiveness. The results of the study show, through capacity building, organizational effectiveness can be improved which further leads to credibility. In fact, the key link to capacity building is not between organizational effectiveness and public confidence, but between organizational capacity and effectiveness. But, through efforts in capacity building, not only does organizational effectiveness becomes improved, the public credibility of the organization is also enhanced, thereby leading to confidence.

Canadian cancer clinics are straining to keep up with growing numbers of patients and, as a result, the capacity to provide follow-up care to cancer patients is being stretched. The Saskatchewan Cancer Agency has structured its community follow-up program to ensure the routine follow-up of patients who have finished active cancer treatments. Follow-up letters are routinely sent to family physicians and some specialists requesting information on the disease status of their cancer patients. For this thesis, I conducted a mail survey of 925 Saskatchewan physicians serving 21,000 patients to learn about general practitioners' and specialists' views of the follow-up program. A 52.5% response rate was achieved. <p>The program was considered useful for 91.5% of physicians, with the follow-up letter serving an important role in reminding physicians to see their cancer patients for follow-up. High percentages of physicians indicated a need for additional patient-specific information (59.3%), clinical information (73.0%) and training (34.9%) to do follow-up. Logistic regression analyses found female gender, a specialty in general practice and lower physician confidence in following cancer to be associated with the need for additional patient information. Lower physician confidence was associated with the need for additional clinical information and a specialty in general practice and lower physician confidence were associated with the need for more training.<p>Percentages of physicians saying they were very confident in following various cancers ranged widely from 19.1% for lymphomas to 54.2% for breast cancer. All regression models regarding physician confidence in following six different cancers had a common correlate: the need for additional training. A physician�s number of follow-up patients was a significant correlate in four of the six regression models and physician specialty was included in half of the models.<p> The results suggest areas of the program and physician need that should be addressed to ensure the delivery of quality follow-up care and the survey findings will be helpful in devising strategies to this end. At the same time, responses indicate the program to be an essential component in the delivery of community-based follow-up care in Saskatchewan.

In statistics it is of interest to find a better interval estimator of the absolute mean deviation. In this thesis, we focus on using the jackknife, the adjusted and the extended jackknife empirical likelihood methods to construct confidence intervals for the mean absolute deviation of a random variable. The empirical log-likelihood ratio statistics is derived whose asymptotic distribution is a standard chi-square distribution. The results of simulation study show the comparison of the average length and coverage probability by using jackknife empirical likelihood methods and normal approximation method. The proposed adjusted and extended jackknife empirical likelihood methods perform better than other methods for symmetric and skewed distributions. We use real data sets to illustrate the proposed jackknife empirical likelihood methods.

The increasing need for more natural human machine interfaces has generated intensive research work directed toward designing and implementing natural speech enabled systems. The Spectrum of speech recognition applications ranges from understanding simple commands to getting all the information in the speech signal such as words, meaning and emotional state of the user. Because it is very hard to constrain a speaker when expressing a voice-based request, speech recognition systems have to be able to handle (by filtering out) out of vocabulary words in the users speech utterance, and only extract the necessary information (keywords) related to the application to deal correctly with the user query. In this thesis, we investigate an approach that can be deployed in keyword spotting systems. We propose a confidence measure feedback module that provides confidence values to be compared against existing Automatic Speech Recognizer word confidences. The feedback module mainly consists of a soft computing tool-based system using fuzzy Gaussian mixture models to identify all English phonemes. Testing has been carried out on the JULIUS system and the preliminary results show that our feedback module outperforms JULIUS confidence measures for both the correct spotted words and the falsely mapped ones. The results obtained could be refined even further using other type of confidence measure and the whole system could be used for a Natural Language Understanding based module for speech understanding applications.