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Titlebook: Basics of Software Engineering Experimentation; Natalia Juristo,Ana M. Moreno Book 2001 Springer-Verlag US 2001 Mathematica.data analysis.

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期刊全稱Basics of Software Engineering Experimentation
影響因子2023Natalia Juristo,Ana M. Moreno
視頻videohttp://file.papertrans.cn/182/181280/181280.mp4
圖書封面Titlebook: Basics of Software Engineering Experimentation;  Natalia Juristo,Ana M. Moreno Book 2001 Springer-Verlag US 2001 Mathematica.data analysis.
影響因子.Basics of Software Engineering Experimentation. is apractical guide to experimentation in a field which has long beenunderpinned by suppositions, assumptions, speculations and beliefs. Itdemonstrates to software engineers how Experimental Design andAnalysis can be used to validate their beliefs and ideas. The bookdoes not assume its readers have an in-depth knowledge of mathematics,specifying the conceptual essence of the techniques to use in thedesign and analysis of experiments and keeping the mathematicalcalculations clear and simple. .Basics of Software EngineeringExperimentation. is practically oriented and is specially writtenfor software engineers, all the examples being based on real andfictitious software engineering experiments.
Pindex Book 2001
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Wolfgang Hauschild,Eberhard Lemkeiments have to be run and how many times the experiments have to be repeated. In other words, a decision is made on how the experiment will actually be arranged. This chapter examines the different kinds of experimental design there are and the circumstances under which each one should be used.
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https://doi.org/10.1007/978-3-663-08544-7g the experiments. So, after completing the unitary experiments, experimenters have a collection of data, called the results of the experimentation. By examining or analysing these data, experimenters will arrive at conclusions about the relationships between factors, the influence of factors on the
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High-Z Materials for X-ray DetectionDesigns of this sort are known as block designs, and the variables whose effect is to be eliminated are known as blocking variables. This chapter discusses the process for analysing data collected from experiments designed thus. Firstly, we will address the case where there is one variable that is n
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Finite domination and Novikov homologyt to find out what impact they have on the response variable, is a factorial design. Designs of this sort study the effect of each factor individually, as well as any interactive influence some factors combined with others could have on the response variable.
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