Breakthroughs in statistics. by Samuel Kotz, Samuel Kotz, Norman L. Johnson

By Samuel Kotz, Samuel Kotz, Norman L. Johnson

This can be the second one of a quantity number of seminal papers within the statistical sciences written up to now a hundred years. those papers have every one had an excellent impact at the improvement of statistical concept and perform over the past century. each one paper is preceded via an advent written through an expert within the box delivering historical past details and assessing its impression. Readers will take pleasure in a clean outlook on now well-established positive factors of statistical thoughts and philosophy through turning into familiar with the methods they've been constructed. it truly is was hoping that a few readers should be encouraged to check the various references supplied within the advent (and additionally within the papers themselves) and so reach a deeper heritage wisdom of the foundation in their paintings.

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This approach to contextual value-added data may well address some of the criticisms voiced about the use of value-added data in the primary sector, although our own experiences in working with primary schools on the RBA Project suggests strongly that value-added analyses are often afforded a status and a degree of objectivity beyond their merits, and are frequently used without discernment and appropriate caution. Equally, there is the possibility that highly valued pupil aptitudes and skills, such as problem-solving, collaboration and decision-making, creativity and imagination, are downplayed and under-valued within such a tightly constrained ethos.

6 Progression of pupils from level 2c at Key Stage 1, 1998, to the expected level (or above) at Key Stage 2, 2002, by gender and ethnicity Percentage of pupils achieving at or above the expected level at KS 2 English Mathematics Science Reading Writing Ethnicity Girls Boys Girls Boys Girls Boys Girls Boys Girls Boys White Indian Pakistani Bangladeshi Black Caribbean Black African Black Other Chinese 70 75 67 84 67 73 73 90 66 71 66 74 54 65 60 79 70 79 71 78 57 66 61 94 85 86 77 85 81 81 85 97 90 90 84 88 84 82 88 92 78 78 72 78 66 71 73 85 59 69 58 67 52 61 56 89 78 76 68 82 73 77 80 92 47 64 60 75 53 58 54 76 36 51 48 57 36 45 33 60 Source: National Statistical Bulletin/DfES (2003).

These include not only factors such as gender, ethnicity, special educational needs, level of free school meals, and EAL (English as an additional language) status, but wider-ranging considerations such as pupils' ages within the school year, a postcode measure of affluence and deprivation, mobility and looked-after-children status. This approach to contextual value-added data may well address some of the criticisms voiced about the use of value-added data in the primary sector, although our own experiences in working with primary schools on the RBA Project suggests strongly that value-added analyses are often afforded a status and a degree of objectivity beyond their merits, and are frequently used without discernment and appropriate caution.

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