991 resultados para Industrial statistics.


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Summary statistics continue to play an important role in identifying and monitoring patterns and trends in educational inequalities between differing groups of pupils over time. However, this article argues that their uncritical use can also encourage the labelling of whole groups of pupils as ‘underachievers’ or ‘overachievers’ as the findings of group-level data are simply applied to individual group members, a practice commonly termed the ‘ecological fallacy’. Some of the adverse consequences of this will be outlined in relation to current debates concerning gender and ethnic differences in educational attainment. It will be argued that one way of countering this uncritical use of summary statistics and the ecological fallacy that it tends to encourage, is to make much more use of the principles and methods of what has been termed ‘exploratory data analysis’. Such an approach is illustrated through a secondary analysis of data from the Youth Cohort Study of England and Wales, focusing on gender and ethnic differences in educational attainment. It will be shown that, by placing an emphasis on the graphical display of data and on encouraging researchers to describe those data more qualitatively, such an approach represents an essential addition to the use of simple summary statistics and helps to avoid the limitations associated with them.

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This study sought to extend earlier work by Mulhern and Wylie (2004) to investigate a UK-wide sample of psychology undergraduates. A total of 890 participants from eight universities across the UK were tested on six broadly defined components of mathematical thinking relevant to the teaching of statistics in psychology - calculation, algebraic reasoning, graphical interpretation, proportionality and ratio, probability and sampling, and estimation. Results were consistent with Mulhern and Wylie's (2004) previously reported findings. Overall, participants across institutions exhibited marked deficiencies in many aspects of mathematical thinking. Results also revealed significant gender differences on calculation, proportionality and ratio, and estimation. Level of qualification in mathematics was found to predict overall performance. Analysis of the nature and content of errors revealed consistent patterns of misconceptions in core mathematical knowledge , likely to hamper the learning of statistics.

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The neglect of a consideration of history has been a feature of mobility research. ‘History’ affects the results of analyses of social mobility by altering the occupational/industrial structure and by encouraging exchange mobility. Changes in industrial structure are rooted more directly in historical causes and can be seen as more fundamental than changes in occupational structure. Following a substantial review of the secondary literature on changes in industrial and occupational structure in Northern Ireland, loglinear analyses of intra- and intergenerational mobility tables for sociologically-derived cohort generations that incorporate occupational and industrial categories are presented. Structural and inheritance effects for industry are as significant as those for occupation. Given the well-established finding of ‘constant social fludity’ in mobility tables once structural effects are controlled, the inclusion of categorization by industry is necessary in order to reach an accurate understanding of occupational mobility and the role of historical change in mobility.