Descriptive Statistics and Linear Regression

This morning Dr. Battle will introduce descriptive statistics and linear regression and how to apply these concepts in mathematical modeling. You will also learn how to use a spreadsheet to help with statistical analysis and to create graphs.

Impact of product-related environmental regulations in Asia : descriptive statistics from a survey of firms in Penang, Malaysia

This paper summarizes the main results of a unique firm survey conducted in Penang, Malaysia in 2012 on product-related environmental regulations. The results show that firms receiving foreign-direct investment have adapted well to regulations but faced more rejections. Several research questions are addressed and examined by using the survey data. Major findings are as follows. First, adaptation involves changes in input procurement and market diversification, which potentially changes the structure of supply chains. Second, belonging to global supply chains is a key factor in compliance, but this requires firms to meet tougher customer requirements. Third, there is much room for government policy to play a role in assisting firms.

Impact of product-related environmental regulations in Asia : descriptive statistics from a survey of firms in Vietnam

This paper summarizes the main results of a unique firm survey conducted in Vietnam in 2011 on product-related environmental regulations (PRERs). The results of this survey are compared with the results of a corresponding survey of firms in Penang, Malaysia (Michida, et al. 2014b). The major findings are as follows. First, adaptation to PRERs involves changes in input procurement and results in market diversification, which potentially alters the structure of supply chains. This finding is consistent with the Malaysian survey result. Second, connections to global supply chains are key to compliance, but this requires firms to meet more stringent customer requirements. Third, government policy can play an important role in assisting firms to comply with PRERs.

Wisconsin trained practical nurses : descriptive statistics.

WI docs. no.: HE 1 ST.6/2:N 83/1971-1976

From inferential statistics to climate knowledge

Climate variability and change are risk factors for climate sensitive activities such as agriculture. Managing these risks requires "climate knowledge", i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Often such information about prognostic variables (e.g. yield, rainfall, run-off) is provided in probabilistic terms (e.g. via cumulative distribution functions, CDF), whereby the quantitative assessments of these alternative management options is based on such CDFs. Sound statistical approaches are needed in order to assess whether difference between such CDFs are intrinsic features of systems dynamics or chance events (i.e. quantifying evidences against an appropriate null hypothesis). Statistical procedures that rely on such a hypothesis testing framework are referred to as "inferential statistics" in contrast to descriptive statistics (e.g. mean, median, variance of population samples, skill scores). Here we report on the extension of some of the existing inferential techniques that provides more relevant and adequate information for decision making under uncertainty.

Application of metabolomics to plant genotype discrimination using statistics and machine learning

Janet Taylor, Ross D King, Thomas Altmann and Oliver Fiehn (2002). Application of metabolomics to plant genotype discrimination using statistics and machine learning. 1st European Conference on Computational Biology (ECCB). (published as a journal supplement in Bioinformatics 18: S241-S248).

Psychology Statistics for Dummies

The quick, easy way to master all the statistics you'll ever need The bad news first: if you want a psychology degree you'll need to know statistics. Now for the good news: Psychology Statistics For Dummies. Featuring jargon-free explanations, step-by-step instructions and dozens of real-life examples, Psychology Statistics For Dummies makes the knotty world of statistics a lot less baffling. Rather than padding the text with concepts and procedures irrelevant to the task, the authors focus only on the statistics psychology students need to know. As an alternative to typical, lead-heavy statistics texts or supplements to assigned course reading, this is one book psychology students won't want to be without. Ease into statistics – start out with an introduction to how statistics are used by psychologists, including the types of variables they use and how they measure them Get your feet wet – quickly learn the basics of descriptive statistics, such as central tendency and measures of dispersion, along with common ways of graphically depicting information Meet your new best friend – learn the ins and outs of SPSS, the most popular statistics software package among psychology students, including how to input, manipulate and analyse data Analyse this – get up to speed on statistical analysis core concepts, such as probability and inference, hypothesis testing, distributions, Z-scores and effect sizes Correlate that – get the lowdown on common procedures for defining relationships between variables, including linear regressions, associations between categorical data and more Analyse by inference – master key methods in inferential statistics, including techniques for analysing independent groups designs and repeated-measures research designs Open the book and find: Ways to describe statistical data How to use SPSS statistical software Probability theory and statistical inference Descriptive statistics basics How to test hypotheses Correlations and other relationships between variables Core concepts in statistical analysis for psychology Analysing research designs Learn to: Use SPSS to analyse data Master statistical methods and procedures using psychology-based explanations and examples Create better reports Identify key concepts and pass your course

Probability and statistics: selected problems

Probability and Statistics—Selected Problems is a unique book for senior undergraduate and graduate students to fast review basic materials in Probability and Statistics. Descriptive statistics are presented first, and probability is reviewed secondly. Discrete and continuous distributions are presented. Sample and estimation with hypothesis testing are presented in the last two chapters. The solutions for proposed excises are listed for readers to references.

The experience of teaching statistics to non-specialist students in Saudi universities

Undoubtedly, statistics has become one of the most important subjects in the modern world, where its applications are ubiquitous. The importance of statistics is not limited to statisticians, but also impacts upon non-statisticians who have to use statistics within their own disciplines. Several studies have indicated that most of the academic departments around the world have realized the importance of statistics to non-specialist students. Therefore, the number of students enrolled in statistics courses has vastly increased, coming from a variety of disciplines. Consequently, research within the scope of statistics education has been able to develop throughout the last few years. One important issue is how statistics is best taught to, and learned by, non-specialist students. This issue is controlled by several factors that affect the learning and teaching of statistics to non-specialist students, such as the use of technology, the role of the English language (especially for those whose first language is not English), the effectiveness of statistics teachers and their approach towards teaching statistics courses, students’ motivation to learn statistics and the relevance of statistics courses to the main subjects of non-specialist students. Several studies, focused on aspects of learning and teaching statistics, have been conducted in different countries around the world, particularly in Western countries. Conversely, the situation in Arab countries, especially in Saudi Arabia, is different; here, there is very little research in this scope, and what there is does not meet the needs of those countries towards the development of learning and teaching statistics to non-specialist students. This research was instituted in order to develop the field of statistics education. The purpose of this mixed methods study was to generate new insights into this subject by investigating how statistics courses are currently taught to non-specialist students in Saudi universities. Hence, this study will contribute towards filling the knowledge gap that exists in Saudi Arabia. This study used multiple data collection approaches, including questionnaire surveys from 1053 non-specialist students who had completed at least one statistics course in different colleges of the universities in Saudi Arabia. These surveys were followed up with qualitative data collected via semi-structured interviews with 16 teachers of statistics from colleges within all six universities where statistics is taught to non-specialist students in Saudi Arabia’s Eastern Region. The data from questionnaires included several types, so different techniques were used in analysis. Descriptive statistics were used to identify the demographic characteristics of the participants. The chi-square test was used to determine associations between variables. Based on the main issues that are raised from literature review, the questions (items scales) were grouped and five key groups of questions were obtained which are: 1) Effectiveness of Teachers; 2) English Language; 3) Relevance of Course; 4) Student Engagement; 5) Using Technology. Exploratory data analysis was used to explore these issues in more detail. Furthermore, with the existence of clustering in the data (students within departments within colleges, within universities), multilevel generalized linear models for dichotomous analysis have been used to clarify the effects of clustering at those levels. Factor analysis was conducted confirming the dimension reduction of variables (items scales). The data from teachers’ interviews were analysed on an individual basis. The responses were assigned to one of the eight themes that emerged from within the data: 1) the lack of students’ motivation to learn statistics; 2) students' participation; 3) students’ assessment; 4) the effective use of technology; 5) the level of previous mathematical and statistical skills of non-specialist students; 6) the English language ability of non-specialist students; 7) the need for extra time for teaching and learning statistics; and 8) the role of administrators. All the data from students and teachers indicated that the situation of learning and teaching statistics to non-specialist students in Saudi universities needs to be improved in order to meet the needs of those students. The findings of this study suggested a weakness in the use of statistical software applications in these courses. This study showed that there is lack of application of technology such as statistical software programs in these courses, which would allow non-specialist students to consolidate their knowledge. The results also indicated that English language is considered one of the main challenges in learning and teaching statistics, particularly in institutions where English is not used as the main language. Moreover, the weakness of mathematical skills of students is considered another major challenge. Additionally, the results indicated that there was a need to tailor statistics courses to the needs of non-specialist students based on their main subjects. The findings indicate that statistics teachers need to choose appropriate methods when teaching statistics courses.

Intensive care nurses' knowledge of enteral nutrition: a descriptive questionnaire

BACKGROUND: Nurses have an important role in the delivery and management of enteral nutrition in critically ill patients, to prevent iatrogenic malnutrition. It is not clear how nurses source enteral nutrition information. 

The guide to the project management body of knowledge (PMBOK Guide) : applicability and contribution to project success in Australia

The PMBOK Guide is one of the most influential publications concerning the knowledge of the project manangement. Moreover, the pervasion of this guide seems to be set to increase as the basis of accreditation - in conjunction with the increasing global trend toward obtaining project management professional status. However, despite the influence and strengthening profile of this guide, reports continue to be published that detail numerous project failures in a wide range of different industries. The PMBOK Guide comprises mainly declarative (know-what) and procedural (know-how) information. In this sense, the guide is largely normative and provides a very good example of the limitations of this approach as highlighted by proponents of a move to the genuine application of positibe theory in project management.----- The aim of this paper is to determine the applicability of the guide in Australia and to determine the extent to which project success can be attributed to the guide. Project Managers from a variety of organisations were surveyed. This postal survey yielded 48 replies. Descriptive statistics was used to assess the incidence and effectivieness of all the processes in the guide. The results indicate that there were no processes that could be considered as peripheral or as a candidate for elimination from the guide. More specifically, all the processes were identified as either a key routine process or a key selective process and positively related to the level of project success. However, the results also indicated that other major factors pertaining to causal knowledge (know-why) are, at least, equally important determinants of project success. It is concluded that declarative, procedural and causal knowledge are all valuable, and given the preponderance of the first two types of knowledge, there seems to be an urgent need to now ensure an equal quest for causal knowledge. In terms of developing causal knowledge, a good starting point would appear to be both positive theory from production and economics.

Research productivity levels of Chinese TEFL academics

Since China’s Economic Reform and its Open Door Policy, China has entered a new era of education (Adamson, 2002; Hu, 2005a). English has gained status as a language for international relations (Graddol, 1997) and international trade (Qu, 2007). Hence, in 2001, China’s Ministry of Education (MOE) required universities to offer 5-10% of their course units in English, particularly in the fields of information technology, biotechnology, finance and law (Jen, 2001; MOE, 2001). However, “the upgrading of national English proficiency, then, is predicted largely on the professional competence of the teaching force” (Hu, 2005b, p. 655). For TEFL academics, one component of this competence is the capacity to conduct research (Day, 1991; Shu, 2002). Indeed, research productivity has become essential for university success, and academics’ employment and promotional prospects. This study aims to investigate 182 Chinese TEFL academics’ research outputs across three Chinese higher education institutions through the research question: What are the research productivity levels of Chinese TEFL academics? A survey instrument was devised to gather TEFL academics’ calculations of research productivity and, in particular, the quality and quantity of research outputs over a five-year period (2004-2008). Descriptive statistics through SPSS were used to analyse data across research output fields (e.g., journal articles, conference papers). Academic status varied (n=182; teaching assistants 23.6%, lecturers 47.3%, associate professors 22.5%, and professors 6.6%) as did years of teaching (1-5 years 27.4%, 6-10 years 24.7%, 11-15 18.1%, 16-20 years 13.7%, > 21 years 15.9%). Results (n=182, male=27%, females=73%) indicated 18% had not produced any research in the five-year period. Indeed, more than 70% had produced no research in all categories except non-core journal articles and provincial projects. An overwhelming majority of TEFL academics had zero productivity in 10 of the 12 categories. Nevertheless, there were highly-productive TEFL academics, who had produced five or more pieces of research across the 12 categories. In addition, there was not much difference between sole and co-authored research outputs, except non-core journal articles where sole authored work was 20% higher than co-authored work. China’s desire for international competitiveness in education will require measures that facilitate higher levels of research productivity. These measures must include professional development, support and mentoring programs, and employment of personnel who can guide these processes. Research performance is an outcome, hence there is a need to understand Chinese TEFL academics’ perceptions about research, and experiences that may hinder and facilitate higher research productivity.

Age-related differences in exercise and quality of life among breast cancer survivors

Purpose: Physical activity has become a focus of cancer recovery research as it has the potential to reduce treatment-related burden and optimize health-related quality of life (HRQoL). However, the potential for physical activity to influence recovery may be age-dependent. This paper describes physical activity levels and HRQoL among younger and older women after surgery for breast cancer and explores the correlates of physical inactivity. Methods: A population-based sample of breast cancer patients diagnosed in South-East Queensland, Australia, (n=287) were assessed once every three months, from 6 to 18 months post-surgery. The Functional Assessment of Cancer Therapy-Breast questionnaire (FACTB+4) and items from the Behavioral Risk Factor Surveillance System (BRFSS) questionnaire were used to measure HRQoL and physical activity, respectively. Physical activity was assigned metabolic equivalent task (MET) values, and categorized as < 3, 3 to 17.9 and 18+ MET-hours/weeks. Descriptive statistics, generalized linear models with age stratification (<50 years versus 50+ years), and logistic regression were used for analyses (p=0.05, two-tailed). Results: Younger women who engaged in 3 or more MET-hours/week of physical activity reported a higher HRQoL at 18 months compared to their more sedentary counterparts (p<0.05). Older women reported similar HRQoL irrespective of activity level and consistently reported clinically higher HRQoL than younger women. Increasing age, being overweight or obese, and restricting use of the treated side at six months post-surgery increased the likelihood of sedentary behavior (OR>3, p<0.05). Conclusions: Age influences the potential to observe HRQoL benefits related to physical activity participation. These results also provide relevant information for the design of exercise interventions for breast cancer survivors and highlights that some groups of women are at greater risk of long-term sedentary behavior.

Trends in demographic, health behaviour factors, and self-perceived weight status : influences on obesity in Australia from 1995 to 2005

Overweight and obesity are two of the most important emerging public health issues in our time and regarded by the World Health Organisation [WHO] (1998) as a worldwide epidemic. The prevalence of obesity in the USA is the highest in the world, and Australian obesity rates fall into second place. Currently, about 60% of Australian adults are overweight (BMI „d 25kg/m2). The socio-demographic factors associated with overweight and/or obesity have been well demonstrated, but many of the existing studies only examined these relationships at one point of time, and did not examine whether significant relationships changed over time. Furthermore, only limited previous research has examined the issue of the relationship between perception of weight status and actual weight status, as well as factors that may impact on people¡¦s perception of their body weight status. Aims: The aims of the proposed research are to analyse the discrepancy between perceptions of weight status and actual weight status in Australian adults; to examine if there are trends in perceptions of weight status in adults between 1995 to 2004/5; and to propose a range of health promotion strategies and furth er research that may be useful in managing physical activity, healthy diet, and weight reduction. Hypotheses: Four alternate hypotheses are examined by the research: (1) there are associations between independent variables (e.g. socio -demographic factors, physical activity and dietary habits) and overweight and/or obesity; (2) there are associations between the same independent variables and the perception of overweight; (3) there are associations between the same independent variables and the discrepancy between weight status and perception of weight status; and (4) there are trends in overweight and/or obesity, perception of overweight, and the discrepancy in Australian adults from 1995 to 2004/5. Conceptual Framework and Methods: A conceptual framework is developed that shows the associations identified among socio -demographic factors, physical activity and dietary habits with actual weight status, as well as examining perception of weight status. The three latest National Health Survey data bases (1995 , 2001 and 2004/5) were used as the primary data sources. A total of 74,114 Australian adults aged 20 years and over were recruited from these databases. Descriptive statistics, bivariate analyses (One -Way ANOVA tests, unpaired t-tests and Pearson chi-square tests), and multinomial logistic regression modelling were used to analyse the data. Findings: This research reveals that gender, main language spoken at home, occupation status, household structure, private health insurance status, and exercise are related to the discrepancy between actual weight status and perception of weight status, but only gender and exercise are related to the discrepancy across the three time point s. The current research provides more knowledge about perception of weight status independently. Factors which affect perception of overweight are gender, age, language spoken at home, private health insurance status, and diet ary habits. The study also finds that many factors that impact overweight and/or obesity also have an effect on perception of overweight, such as age, language spoken at home, household structure, and exercise. However, some factors (i.e. private health insurance status and milk consumption) only impact on perception of overweight. Furthermore, factors that are rel ated to people’s overweight are not totally related to people’s underestimation of their body weight status in the study results. Thus, there are unknown factors which can affect people’s underestimation of their body weight status. Conclusions: Health promotion and education activities should provide education about population health education and promotion and education for particular at risk sub -groups. Further research should take the form of a longitudinal study design ed to examine the causal relationship between overweight and/or obesity and underestimation of body weight status, it should also place more attention on the relationships between overweight and/or obesity and dietary habits, with a more comprehensive representation of SES. Moreover, further research that deals with identification of characteristics about perception of weight status, in particular the underestimation of body weight status should be undertaken.