By Э. Боума, Т.Б. Клементьева

Книга Animals. Животные Animals. Животные Книги Иностранные языки Автор: Э. Боума, Т.Б. Клементьева Год издания: 2008 Формат: pdf Издат.:Аст-пресс школа Страниц: 48+17 Размер: eighty five Язык: Английский0 (голосов: zero) Оценка:Новый игровой курс английского языка "Животные" знакомит детей с разнообразным миром животных, учит называть по-английски обитателей фермы; зверей, птиц, насекомых леса, зоопарка; морских обитателей, а также ребята запомнят множество новых глаголов и прилагательных. Песни, стихи, подвижные и пальчиковые игры, весёлые задания делают процесс изучения увлекательным. Вкомплекте: книгаученика и рабочая тетрадь. Для детей дошкольного и младшего школьного возраста (4-7 лет).

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We will be using the coefficient of variation in calculating sample sizes in some examples later in this book. Let us review what we have learned to this point about the sampling distribution of abundance estimates. First of all, assuming an adequate sample size, the sampling distribution approximates a normal distribution regardless of the underlying spatial distribution of animals. Second, if we convert the values of the sampling distribution into z values, these values will approximate a standard normal distribution with mean 0 and standard deviation 1.

This is obviously not a good property. A possible remedy for this is to use a bootstrapping approach to generate confidence intervals, which we will discuss next. '^Note that Fig. , a continuous distribution characterized by a solid line), whereas Fig. e.. finite or discrete distributions). However, we can use the properties of the theoretical distribution as an approximation. 17 ments. ^ • • • • » • • • • » « 1 • • • < • \ # ^^ • ' 1 ^9 ft 1 • » # • • • __JL A sampling frame of 100 plots with an underlying clumped distribution of ele- To this point, we have used properties of external or reference distributions to produce measures of how close our sample-based abundance estimate is to the true abundance.

Further, magnitude of bias can be assessed directly only through comparisons either between the sample estimate and the true value of the parameter or between the biased sample estimate and an unbiased sample estimate (Yates, 1981). A census would be required to obtain the true value of the parameter, which is very unlikely. One may as well have obtained an unbiased estimate to begin with rather than obtaining one for comparative purposes. Uncorrected bias could have serious consequences regarding validity and usefulness of parameter estimates.

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