Titlebook: A First Course in Statistical Inference; Jonathan Gillard Textbook 2020 Springer Nature Switzerland AG 2020 Statistical inference.confiden

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One-Way Analysis of Variance (ANOVA),eived by the neoclassical approach. Her analysis reveals that these approaches arrive at contrasting results with regard to deception. Whereas in the former deception is vital to an understanding of exchange, the latter regards deception as an inefficiency, hindering exchange and ultimately making it impossib978-1-4419-5301-8978-1-4757-3470-6

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Einführung in die Swap-Gesch?fteossibly unknown population parameters. Classical results about the sample mean and sample variance are stated, and here famous continuous distributions which are the cornerstone for statistical inference are described: Normal, Student’s t, the chi-squared, and F. One of the most important results in

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,Computergestützte Aktienanalyse,othesis testing. In this chapter, we introduce much of the terminology associated with hypothesis testing, such as Type I error, Type II error, significance level, power, and p-value. We use lots of examples to illuminate the concepts and the methodology.

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Aktien-, Zins- und W?hrungsderivateThis chapter gives a brief recap of key ideas from elementary probability theory that will be used throughout the book. Specifically, this chapter will describe discrete and continuous random variables and probability mass/density functions, and how to compute the mean and variance of random variables.

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