907 resultados para General Linear Methods
Resumo:
Mode of access: Internet.
Resumo:
Treasury Dept. Doc. no. 71. Coast and Geodetic Survey.
Resumo:
On cover: Reviewed by George F. Barrett, attorney general.
Resumo:
Publisher's advertisement on back cover.
Resumo:
Cover title.
Resumo:
Paged continuously.
Resumo:
Mode of access: Internet.
Resumo:
Mode of access: Internet.
Resumo:
On spine: Shunk on railway curves &c.
Resumo:
Mode of access: Internet.
Resumo:
Cover title.
Resumo:
This paper begins by suggesting that when considering Corporate Social Responsibility (CSR), even CSR as justified in terms of the business case, stakeholders are of great importance to corporations. In the UK the Company Law Review (DTI, 2002) has suggested that it is appropriate for UK companies to be managed upon the basis of an enlightened shareholder approach. Within this approach the importance of stakeholders, other than shareholders, is recognised as being instrumental in succeeding in providing shareholder value. Given the importance of these other stakeholders it is then important that corporate management measure and manage stakeholder performance. In order to do this there are two general approaches that could be adopted and these are the use of monetary values to reflect stakeholder value or cost and non-monetary values. In order to consider these approaches further this paper considered the possible use of these approaches for two stakeholder groups: namely employees and the environment. It concludes that there are ethical and practical difficulties with calculating economic values for stakeholder resources and so prefers a multi-dimensional approach to stakeholder performance measurement that does not use economic valuation.
Resumo:
In some circumstances, there may be no scientific model of the relationship between X and Y that can be specified in advance and indeed the objective of the investigation may be to provide a ‘curve of best fit’ for predictive purposes. In such an example, the fitting of successive polynomials may be the best approach. There are various strategies to decide on the polynomial of best fit depending on the objectives of the investigation.
Resumo:
Multiple regression analysis is a complex statistical method with many potential uses. It has also become one of the most abused of all statistical procedures since anyone with a data base and suitable software can carry it out. An investigator should always have a clear hypothesis in mind before carrying out such a procedure and knowledge of the limitations of each aspect of the analysis. In addition, multiple regression is probably best used in an exploratory context, identifying variables that might profitably be examined by more detailed studies. Where there are many variables potentially influencing Y, they are likely to be intercorrelated and to account for relatively small amounts of the variance. Any analysis in which R squared is less than 50% should be suspect as probably not indicating the presence of significant variables. A further problem relates to sample size. It is often stated that the number of subjects or patients must be at least 5-10 times the number of variables included in the study.5 This advice should be taken only as a rough guide but it does indicate that the variables included should be selected with great care as inclusion of an obviously unimportant variable may have a significant impact on the sample size required.