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Titlebook: Regression Analysis; Theory, Methods and Ashish Sen,Muni Srivastava Book 1990 Springer Science+Business Media New York 1990 Fitting.Random

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發(fā)表于 2025-3-21 19:22:32 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Regression Analysis
副標題Theory, Methods and
編輯Ashish Sen,Muni Srivastava
視頻videohttp://file.papertrans.cn/826/825508/825508.mp4
叢書名稱Springer Texts in Statistics
圖書封面Titlebook: Regression Analysis; Theory, Methods and  Ashish Sen,Muni Srivastava Book 1990 Springer Science+Business Media New York 1990 Fitting.Random
描述Any method of fitting equations to data may be called regression. Such equations are valuable for at least two purposes: making predictions and judging the strength of relationships. Because they provide a way of em- pirically identifying how a variable is affected by other variables, regression methods have become essential in a wide range of fields, including the soeial seiences, engineering, medical research and business. Of the various methods of performing regression, least squares is the most widely used. In fact, linear least squares regression is by far the most widely used of any statistical technique. Although nonlinear least squares is covered in an appendix, this book is mainly ab out linear least squares applied to fit a single equation (as opposed to a system of equations). The writing of this book started in 1982. Since then, various drafts have been used at the University of Toronto for teaching a semester-Iong course to juniors, seniors and graduate students in a number of fields, including statistics, pharmacology, pharmacology, engineering, economics, forestry and the behav- ioral seiences. Parts of the book have also been used in a quarter-Iong course given to M
出版日期Book 1990
關鍵詞Fitting; Random variable; Regression analysis; Variance; best fit; correlation; derivative; distribution; no
版次1
doihttps://doi.org/10.1007/978-3-662-25092-1
isbn_softcover978-3-540-97211-2
isbn_ebook978-3-662-25092-1Series ISSN 1431-875X Series E-ISSN 2197-4136
issn_series 1431-875X
copyrightSpringer Science+Business Media New York 1990
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沙發(fā)
發(fā)表于 2025-3-21 21:47:39 | 只看該作者
Book 1990 of Toronto for teaching a semester-Iong course to juniors, seniors and graduate students in a number of fields, including statistics, pharmacology, pharmacology, engineering, economics, forestry and the behav- ioral seiences. Parts of the book have also been used in a quarter-Iong course given to M
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發(fā)表于 2025-3-22 03:27:52 | 只看該作者
Introduction,uences of our actions and to manipulate our environment. Most relationships we know of are based on empirical observations. Although some relationships are postulated on theoretical grounds, usually the theories themselves were originally obtained from empirical observations. And even these relationships often need to be empirically tested.
地板
發(fā)表于 2025-3-22 07:31:25 | 只看該作者
Multiple Regression,rst to simple regression, which we considered in Chapter 1, and then to multiple regression. After that we shall derive formulae for least squares estimates and present properties of these estimates. These properties will be derived under the Gauss-Markov conditions which were presented in Chapter 1 and are essentially restated in Section 2.5.
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Unequal Variances,re. These conditions can be checked and if we find that one or more of them are seriously violated, we can take action that will cause at least approximate compliance. This and the next few chapters will deal with various ways in which these G-M conditions can be violated and what we would then need to do.
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Tests and Confidence Regions,Consider the example of house prices that we saw in the last chapter. It is reasonable to ask one or more of the following questions:
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