標(biāo)題: Titlebook: Analysis of Variance in Experimental Design; Harold R. Lindman Textbook 1992 Springer-Verlag New York, Inc. 1992 Factor.Matrix.SAS.Statist [打印本頁] 作者: 熱情美女 時間: 2025-3-21 18:49
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書目名稱Analysis of Variance in Experimental Design讀者反饋學(xué)科排名
作者: 玷污 時間: 2025-3-21 23:47
Nested Designs,tain scores in every cell. This chapter and the next discuss some designs in which not all cells contain scores. These . are convenient for some purposes, but they also have disadvantages. When choosing a design, the advantages and disadvantages must be weighed against each other.作者: meritorious 時間: 2025-3-22 00:35
Basic Matrix Algebra, know no matrix algebra, it should teach you enough to understand the remaining chapters. If you are not sure of your knowledge of matrix algebra, you should probably at least scan this material. If you already have a basic knowledge of matrix algebra, you may skip most of this chapter, although you should read at least the last section.作者: 荒唐 時間: 2025-3-22 07:35 作者: EXCEL 時間: 2025-3-22 09:04 作者: Encoding 時間: 2025-3-22 13:00
The Ethics of Advocacy and Consent,tain scores in every cell. This chapter and the next discuss some designs in which not all cells contain scores. These . are convenient for some purposes, but they also have disadvantages. When choosing a design, the advantages and disadvantages must be weighed against each other.作者: 內(nèi)閣 時間: 2025-3-22 18:14
E. C. Jansen,K. Jansen,J. Pedersen know no matrix algebra, it should teach you enough to understand the remaining chapters. If you are not sure of your knowledge of matrix algebra, you should probably at least scan this material. If you already have a basic knowledge of matrix algebra, you may skip most of this chapter, although you should read at least the last section.作者: 慎重 時間: 2025-3-22 22:00
https://doi.org/10.1007/978-1-4613-9722-9Factor; Matrix; SAS; Statistica; Variance; algebra; analysis of variance; boundary element method; field; mod作者: 凹槽 時間: 2025-3-23 02:05 作者: 出價 時間: 2025-3-23 08:12 作者: 約會 時間: 2025-3-23 12:53 作者: Volatile-Oils 時間: 2025-3-23 14:48 作者: 捏造 時間: 2025-3-23 19:14 作者: Lasting 時間: 2025-3-24 00:57 作者: thyroid-hormone 時間: 2025-3-24 02:57
Introducing a Theoretical Travel Guide,.. Whenever the factors in a design are not completely crossed, some effects will be confounded. However, in some designs the factors are neither completely crossed nor completed nested. The 4 × 6 design in Table 9.1 is an example; in this design, the factors are not completely crossed, yet neither 作者: 祖先 時間: 2025-3-24 07:53
W. W. Buchanan,P. J. Rooney,G. Kraagg”) of a learned response after 10, 20, 30, 40, 50, and 60 learning trials. The six numbers of learning trials are the six levels of the factor being studied; the data are the numbers of trials to extinction. The labels on the factor levels in this experiment are meaningful numerical values: Thirty 作者: hangdog 時間: 2025-3-24 10:51 作者: 退潮 時間: 2025-3-24 15:18
E. C. Jansen,K. Jansen,J. Pedersen know no matrix algebra, it should teach you enough to understand the remaining chapters. If you are not sure of your knowledge of matrix algebra, you should probably at least scan this material. If you already have a basic knowledge of matrix algebra, you may skip most of this chapter, although you作者: 窒息 時間: 2025-3-24 19:49
J. Perry,E. Bontgrager,D. Antonellie dependent variable. The two examples in Chapter 12 are illustrative. In Table 12.2 the experiment of Table 2.1 is extended to include measures of IQ and chronological age as well as of intellectual maturity. There are thus three dependent variables. In Table 12.3 the data in Table 5.1 are extended作者: ensemble 時間: 2025-3-24 23:30
G. Fernie,J. Holden,R. Lobb,M. Sotosting for others. If we cannot control for certain variables experimentally by making them the levels of a factor, we may be able to control for them statistically by analysis of covariance. In this chapter, we will first give a simple example. We will then describe the model for analysis of covaria作者: 偏狂癥 時間: 2025-3-25 04:24
The Disabled Person as a Witness in Courthese are instances of the .. The . general linear model is most easily represented in matrix terms as . where . is a vector of . observed scores, . is a vector of . unknown parameters, . is an . × . matrix of coefficients, and . is a vector of . random errors. (In this chapter . is a scalar represen作者: –LOUS 時間: 2025-3-25 09:22 作者: GRIPE 時間: 2025-3-25 12:09 作者: Magnificent 時間: 2025-3-25 18:17
https://doi.org/10.1057/9780230393530In the simplest version of the . test, the means of two independent groups of scores are compared. The simplest form of the ., or ., is an extension of the . test to the comparison of more than two groups. For example, consider the data in Table 2.1.作者: 保守黨 時間: 2025-3-25 21:46 作者: 破布 時間: 2025-3-26 00:22
Review of Statistical Concepts,This text is written for those who have already had an intermediate level, noncalculus course in statistics. In this chapter we will review certain basic concepts and cover some fine points that may have been overlooked in earlier study. This chapter will also introduce the special notation used in the book, and my own statistical biases.作者: accordance 時間: 2025-3-26 08:18
Analysis of Variance, One-Way, Fixed Effects,In the simplest version of the . test, the means of two independent groups of scores are compared. The simplest form of the ., or ., is an extension of the . test to the comparison of more than two groups. For example, consider the data in Table 2.1.作者: 考古學(xué) 時間: 2025-3-26 12:03 作者: 確保 時間: 2025-3-26 14:39
Random Effects,rugs. In some cases, however, the groups or “treatments” themselves may have been selected randomly from a large number of potential treatments. In this chapter we will consider methods for analyzing such data.作者: 發(fā)起 時間: 2025-3-26 19:12 作者: Leaven 時間: 2025-3-26 21:03 作者: DEMUR 時間: 2025-3-27 01:14 作者: 可觸知 時間: 2025-3-27 08:31 作者: 通情達(dá)理 時間: 2025-3-27 12:23 作者: 領(lǐng)袖氣質(zhì) 時間: 2025-3-27 14:01
Introducing a Theoretical Travel Guide,letely crossed nor completed nested. The 4 × 6 design in Table 9.1 is an example; in this design, the factors are not completely crossed, yet neither is nested within the other. The analysis of most such . designs is very difficult, but for certain designs it is relatively simple.作者: 返老還童 時間: 2025-3-27 19:39 作者: DAMP 時間: 2025-3-27 23:12 作者: 動物 時間: 2025-3-28 03:21
Other Multiple Comparison Methods,on the basis of apparent differences among the obtained means would introduce a strong bias in favor of rejecting the null hypothesis. Other techniques for making multiple comparisons exist, but they have very low power; in many cases, they will not find a significant difference unless it is large enough to be obvious without a test.作者: AXIOM 時間: 2025-3-28 10:01
Other Incomplete Designs,letely crossed nor completed nested. The 4 × 6 design in Table 9.1 is an example; in this design, the factors are not completely crossed, yet neither is nested within the other. The analysis of most such . designs is very difficult, but for certain designs it is relatively simple.作者: 粉筆 時間: 2025-3-28 12:25 作者: certitude 時間: 2025-3-28 18:26
General Linear Model, a vector of . unknown parameters, . is an . × . matrix of coefficients, and . is a vector of . random errors. (In this chapter . is a scalar representing the total number of scores; . represents the number of scores in each group.)作者: 保守 時間: 2025-3-28 19:55
Textbook 1992es enough theory to enable the reader to apply the methods intelligently rather than mechanically. Comprehensive, and covering the important techniques in the field, including new methods of post hoc testing. The relationships between different research designs are emphasized, and these relationship作者: 表臉 時間: 2025-3-28 22:53
https://doi.org/10.1007/978-3-322-94971-4e not planned, but were suggested by the data. Both kinds of techniques are useful. In a well-planned experiment there are often specific differences in which we are interested; however, we should also be aware of unexpected differences in the data.作者: 容易做 時間: 2025-3-29 05:51
W. W. Buchanan,P. J. Rooney,G. Kraag those in Figure 10.1 (taken from the data in Table 10.1); in this graph the numerical values of the factor levels dictate both their order and their spacing along the . axis. By contrast, for the data plotted in Figure 3.1, both the ordering and the spacing of the factor levels were arbitrary.作者: 小步舞 時間: 2025-3-29 09:55 作者: 閃光東本 時間: 2025-3-29 14:55
Comparing Groups,e not planned, but were suggested by the data. Both kinds of techniques are useful. In a well-planned experiment there are often specific differences in which we are interested; however, we should also be aware of unexpected differences in the data.作者: mettlesome 時間: 2025-3-29 17:49
One-Way Designs with Quantitative Factors, those in Figure 10.1 (taken from the data in Table 10.1); in this graph the numerical values of the factor levels dictate both their order and their spacing along the . axis. By contrast, for the data plotted in Figure 3.1, both the ordering and the spacing of the factor levels were arbitrary.作者: 附錄 時間: 2025-3-29 20:12
Analysis of Covariance,riance, as compared with other possible ways of solving the same problem. Finally, we will describe the general analysis of covariance, with examples. The reader who wants only a general understanding of analysis of covariance can skip the final section.作者: 來這真柔軟 時間: 2025-3-30 03:58
https://doi.org/10.1007/978-3-319-65175-0rugs. In some cases, however, the groups or “treatments” themselves may have been selected randomly from a large number of potential treatments. In this chapter we will consider methods for analyzing such data.作者: 巫婆 時間: 2025-3-30 07:38 作者: Collected 時間: 2025-3-30 09:02 作者: obnoxious 時間: 2025-3-30 12:59
