P value and the theory of hypothesis testing: an explanation for new researchers.

In the 1920s, Ronald Fisher developed the theory behind the p value and Jerzy Neyman and Egon Pearson developed the theory of hypothesis testing. These distinct theories have provided researchers important quantitative tools to confirm or refute their hypotheses. The p value is the probability to obtain an effect equal to or more extreme than the one observed presuming the null hypothesis of no effect is true; it gives researchers a measure of the strength of evidence against the null hypothesis. As commonly used, investigators will select a threshold p value below which they will reject the null hypothesis. The theory of hypothesis testing allows researchers to reject a null hypothesis in favor of an alternative hypothesis of some effect. As commonly used, investigators choose Type I error (rejecting the null hypothesis when it is true) and Type II error (accepting the null hypothesis when it is false) levels and determine some critical region. If the test statistic falls into that critical region, the null hypothesis is rejected in favor of the alternative hypothesis. Despite similarities between the two, the p value and the theory of hypothesis testing are different theories that often are misunderstood and confused, leading researchers to improper conclusions. Perhaps the most common misconception is to consider the p value as the probability that the null hypothesis is true rather than the probability of obtaining the difference observed, or one that is more extreme, considering the null is true. Another concern is the risk that an important proportion of statistically significant results are falsely significant. Researchers should have a minimum understanding of these two theories so that they are better able to plan, conduct, interpret, and report scientific experiments.

Handbook of life design : from practice to theory and from theory to practice

Our lives and careers are becoming ever more unpredictable. The "life-design paradigm" described in detail in this ground-breaking handbook helps counselors and others meet people's increasing need to develop and manage their own lives and careers. Life-design interventions, suited to a wide variety of cultural settings, help individuals become actors in their own lives and careers by activating, stimulating, and developing their personal resources. This handbook first addresses life-design theory, then shows how to apply life designing to different age groups and with more at-risk people, and looks at how to train life-design counselors

Analysis of a finite volume method for a cross-diffusion model in population dynamics

The main goal of this paper is to propose a convergent finite volume method for a reactionâeuro"diffusion system with cross-diffusion. First, we sketch an existence proof for a class of cross-diffusion systems. Then the standard two-point finite volume fluxes are used in combination with a nonlinear positivity-preserving approximation of the cross-diffusion coefficients. Existence and uniqueness of the approximate solution are addressed, and it is also shown that the scheme converges to the corresponding weak solution for the studied model. Furthermore, we provide a stability analysis to study pattern-formation phenomena, and we perform two-dimensional numerical examples which exhibit formation of nonuniform spatial patterns. From the simulations it is also found that experimental rates of convergence are slightly below second order. The convergence proof uses two ingredients of interest for various applications, namely the discrete Sobolev embedding inequalities with general boundary conditions and a space-time $L^1$ compactness argument that mimics the compactness lemma due to Kruzhkov. The proofs of these results are given in the Appendix.

A test of Jessor's problem behavior theory in a Eurasian and a Western European developmental context.

PURPOSE: The current study tested the applicability of Jessor's problem behavior theory (PBT) in national probability samples from Georgia and Switzerland. Comparisons focused on (1) the applicability of the problem behavior syndrome (PBS) in both developmental contexts, and (2) on the applicability of employing a set of theory-driven risk and protective factors in the prediction of problem behaviors. METHODS: School-based questionnaire data were collected from n = 18,239 adolescents in Georgia (n = 9499) and Switzerland (n = 8740) following the same protocol. Participants rated five measures of problem behaviors (alcohol and drug use, problems because of alcohol and drug use, and deviance), three risk factors (future uncertainty, depression, and stress), and three protective factors (family, peer, and school attachment). Final study samples included n = 9043 Georgian youth (mean age = 15.57; 58.8% females) and n = 8348 Swiss youth (mean age = 17.95; 48.5% females). Data analyses were completed using structural equation modeling, path analyses, and post hoc z-tests for comparisons of regression coefficients. RESULTS: Findings indicated that the PBS replicated in both samples, and that theory-driven risk and protective factors accounted for 13% and 10% in Georgian and Swiss samples, respectively in the PBS, net the effects by demographic variables. Follow-up z-tests provided evidence of some differences in the magnitude, but not direction, in five of six individual paths by country. CONCLUSION: PBT and the PBS find empirical support in these Eurasian and Western European samples; thus, Jessor's theory holds value and promise in understanding the etiology of adolescent problem behaviors outside of the United States.

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

Capitalism in the classroom : the impact of self-enhancement values and normative assessment on student motivation, goals and attitudes towards cheating

Abstract The neo-liberal capitalist ideology has come under heavy fire with anecdotal evidence indicating a link between these same values and unethical behavior. Academic institutions reflect social values and act as socializing agents for the young. Can this explain the high and increasing rates of cheating that currently prevail in education? Our first chapter examines the question of whether self-enhancement values of power and açhievement, the individual level equivalent of neo-liberal capitalist values, predict positive attitudes towards cheating. Furthermore, we explore the mediating role of motivational factors. Results of four studies reveal that self-enhancement value endorsement predicts the adoption of performance-approach goals, a relationship mediated by introjected regulation, namely desire for social approval and that self-enhancement value endorsement also predicts the condoning of cheating, a relationship mediated by performance-approach goal adoption. However, self-transcendence values prescribed by a normatively salient source have the potential to reduce the link between self-enhancement value endorsément and attitudes towards cheating. Normative assessment constitutes a key tool used by academic institutions to socialize young people to accept the competitive, meritocratic nature of a sociéty driven by a neo-liberal capitalist ideology. As such, the manifest function of grades is to motivate students to work hard and to buy into the competing ethos. Does normative assessment fulfill these functions? Our second chapter explores the reward-intrinsic motivation question in the context of grading, arguably a high-stakes reward. In two experiments, the relative capacity of graded high performance as compared to the task autonomy experienced in an ungraded task to predict post-task intrinsic motivation is assessed. Results show that whilst the graded task performance predicts post-task appreciation, it fails to predict ongoing motivation. However, perceived autonomy experienced in non-graded condition, predicts both post-task appreciation and ongoing motivation. Our third chapter asks whether normative assessment inspires the spirit of competition in students. Results of three experimental studies reveal that expectation of a grade for a task, compared to no grade, induces greater adoption of performance-avoidance, but not performance-approach, goals. Experiment 3 provides an explanatory mechanism for this, showing that reduced autonomous motivation experienced in previous graded tasks mediates the relationship between grading and adoption of performance avoidance goals in a subsequent task. The above results, when combined, provide evidence as to the deleterious effects of self enhancement values and the associated practice of normative assessment in school on student motivation, goals and ethics. We conclude by using value and motivation theory to explore solutions to this problem.

Effect of an ectoparasite on lay date, nest-site choice, desertion, and hatching success in the great tit (Parus major)

Ectoparasites are common in most bird species, but experimental evidence of their effects on life-history traits is scarce. We investigated experimentally the effects of the hematophagous hen flea (Ceratophyllus gallinae) on timing of reproduction, nest-site choice, nest desertion, clutch size, and hatching success in the great tit (Parus major). When great tits were offered a choice on their territory between an infested and a parasite-free nest-box, they chose the one without parasites. When there was no choice, the great tits in a territory containing an infested nest-box delayed laying the clutch by 11 days as compared with the birds that were offered a parasite-free nesting opportunity. The finding that there was no difference in phenotypic traits related to dominance between the birds nesting in infested boxes and birds nesting in parasite-free boxes suggests that the delay is not imposed by social dominance. Nest desertion between laying and shortly after hatching was significandy higher in infested nests. There was no difference between infested and parasite-free nests in clutch size, but hatching success and hence brood size at hatching were significantly smaller in infested nests. Nest-box studies of great tits have been seminal in the development of evolutionary, ecological, and behavioral theory, but recently a polemic has arisen in the literature about the validity of the conclusions drawn from nest-box studies where the naturally occurring, detrimental ectoparasites are eliminated by the routine removal of old nests between breeding seasons. Our study suggests that this criticism is valid and that the evaluation of the effects of ectoparasites may improve our understanding of behavioral traits, life-history traits, or population dynamics