991 resultados para Children statistics


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This paper argues for a renewed focus on statistical reasoning in the elementary school years, with opportunities for children to engage in data modeling. Data modeling involves investigations of meaningful phenomena, deciding what is worthy of attention, and then progressing to organizing, structuring, visualizing, and representing data. Reported here are some findings from a two-part activity (Baxter Brown’s Picnic and Planning a Picnic) implemented at the end of the second year of a current three-year longitudinal study (grade levels 1-3). Planning a Picnic was also implemented in a grade 7 class to provide an opportunity for the different age groups to share their products. Addressed here are the grade 2 children’s predictions for missing data in Baxter Brown’s Picnic, the questions posed and representations created by both grade levels in Planning a Picnic, and the metarepresentational competence displayed in the grade levels’ sharing of their products for Planning a Picnic.

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Includes bibliography

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This article draws attention to the importance of routinely collected administrative data as an important source for understanding the characteristics of the Northern Ireland child welfare system as it has developed since the Children (Northern Ireland) Order 1995 became its legislative base. The article argues that the availability of such data is a strength of the Northern Ireland child welfare system and urges local politicians, lobbyists, researchers, policy-makers, operational managers, practitioners and service user groups to make more use of them. The main sources of administrative data are identified. Illustration of how these can be used to understand and to ask questions about the system is provided by considering some of the trends since the Children Order was enacted. The “protection” principle of the Children Order provides the focus for the illustration. The statistical trends considered relate to child protection referrals, investigations and registrations and to children and young people looked after under a range of court orders available to ensure their protection and well-being.

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An educational priority of many nations is to enhance mathematical learning in early childhood. One area in need of special attention is that of statistics. This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling activities. Such modelling involves investigations of meaningful phenomena, deciding what is worthy of attention (i.e., identifying complex attributes), and then progressing to organising, structuring, visualising, and representing data. Results are reported from the first year of a three-year longitudinal study in which three classes of first-grade children and their teachers engaged in activities that required the creation of data models. The theme of “Looking after our Environment,” a component of the children’s science curriculum at the time, provided the context for the activities. Findings focus on how the children dealt with given complex attributes and how they generated their own attributes in classifying broad data sets, and the nature of the models the children created in organising, structuring, and representing their data.

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This thesis explored the knowledge and reasoning of young children in solving novel statistical problems, and the influence of problem context and design on their solutions. It found that young children's statistical competencies are underestimated, and that problem design and context facilitated children's application of a wide range of knowledge and reasoning skills, none of which had been taught. A qualitative design-based research method, informed by the Models and Modeling perspective (Lesh & Doerr, 2003) underpinned the study. Data modelling activities incorporating picture story books were used to contextualise the problems. Children applied real-world understanding to problem solving, including attribute identification, categorisation and classification skills. Intuitive and metarepresentational knowledge together with inductive and probabilistic reasoning was used to make sense of data, and beginning awareness of statistical variation and informal inference was visible.

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The method of generalized estimating equations (GEE) is a popular tool for analysing longitudinal (panel) data. Often, the covariates collected are time-dependent in nature, for example, age, relapse status, monthly income. When using GEE to analyse longitudinal data with time-dependent covariates, crucial assumptions about the covariates are necessary for valid inferences to be drawn. When those assumptions do not hold or cannot be verified, Pepe and Anderson (1994, Communications in Statistics, Simulations and Computation 23, 939–951) advocated using an independence working correlation assumption in the GEE model as a robust approach. However, using GEE with the independence correlation assumption may lead to significant efficiency loss (Fitzmaurice, 1995, Biometrics 51, 309–317). In this article, we propose a method that extracts additional information from the estimating equations that are excluded by the independence assumption. The method always includes the estimating equations under the independence assumption and the contribution from the remaining estimating equations is weighted according to the likelihood of each equation being a consistent estimating equation and the information it carries. We apply the method to a longitudinal study of the health of a group of Filipino children.

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The purpose of this study was to evaluate the validity and inter-rater reliability of the Observation System for Recording Activity in Children: Youth Sports (OSRAC:YS). Children (N=29) participating in a parks and recreation soccer program were observed during regularly scheduled practices. Physical activity (PA) intensity and contextual factors were recorded by momentary time-sampling procedures (10-sec observe, 20-sec record). Two observers simultaneously observed and recorded children's PA intensity, practice context, social context, coach behavior, and coach proximity. Inter-rater reliability was based on agreement (Kappa) between the observer's coding for each category, and the Intraclass Correlation Coefficient (ICC) for percent of time spent in MVPA. Validity was assessed by calculating the correlation between OSRAC:YS estimated and objectively measured MVPA. Kappa statistics for each category demonstrated substantial to almost perfect inter-observer agreement (Κappa = 0.67 to 0.93). The ICC for percent time in MVPA was 0.76 (95% C.I. = 0.49 - 0.90). A significant correlation (r = 0.73) was observed for MVPA recorded by observation and MVPA measured via accelerometry. The results indicate the OSRAC:YS is a reliable and valid tool for measuring children's PA and contextual factors during a youth soccer practice.

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Three core components in developing children’s understanding and appreciation of data — establish a context, pose and answer statistical questions, represent and interpret data — lay the foundation for the fourth component: use data to enhance existing context.

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This is the protocol for a review and there is no abstract. The objectives are as follows: This overview intends to: a) summarise the existing evidence on interventions that aim to increase PA; b) explore whether any effects of the intervention are different within and between populations, and whether these differences form an equity gradient such as an effect that differs according the advantage/disadvantage (e.g. low income and ethnic minorities); c) highlight gaps in the present evidence base that may warrant a Cochrane systematic review to be completed; and c) identify 'up to date' Cochrane reviews. .

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This study aimed to quantify the intensity of physical activity (PA) of children during school recess (RE), compare the AF gender and seasonal influences. The sample consisted of 30 girls (11.2 ± 1.3 years) and 20 boys (11.3 ± 0.8 years). Heart rate was monitored for three consecutive REs in winter (INV) and spring (PRI) with intensity of the activity being classified as low, moderate and vigorous. Descriptive statistics were used for general data, t test for independent samples for differences between the sexes, paired t test for seasonality. Differences were found between INV and PRI temperatures. Girls had a significant reduction in the AF INV to PRI, which was not observed among boys. The RE represented a small contribution to daily recommendations of AF.

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The aim of the study was to determine the reliability of body mass index based (BMI) cutoff values in diagnosing obesity among Sri Lankan children. Height, weight, waist circumference (WC) and hip circumference (HC) in 282 children were measured. Total body water was determined by deuterium dilution and fat mass (FM) derived using age and gender specific constants. A percentage FM of 30% for girls and 25% for boys were considered as cutoff levels for obesity. Two hundred and eighty two children (M/F: 158/124) were studied and 99 (80%) girls and 72 (45.5%) boys were obese based on % body fat. Eight (6.4%) girls and nine (5.7%) boys were obese based on International Obesity Task Force (IOTF) cutoff values. Percentage FM and WC centile charts were able to diagnose a significant proportion of children as true obese children. The FM and BMI were closely associated in both girls (r = 0.82, p < 0.001) and boys (r = 0.87, p < 0.001). Percentage FM and BMI had a very low but significant association; girls (r = 0.32, p < 0.001) and boys (r = 0.68, p < 0.001). FM had a significant association with WC and HC. BMI based cutoff values had a specificity of 100% but a very low sensitivity, varying between 8% and 23.6%. BMI is a poor indicator of the percentage fat and the commonly used cutoff values were not sensitive to detect cases of childhood obesity in Sri Lankan children.