How to use unbiasedly in a sentence? Find typical usage patterns (collocations)/phrases/context for "unbiasedly" and check conjugation/comparative form for "unbiasedly". Mastering all the usages of "unbiasedly" from sentence examples published by news publications.
"Our aim is to inspire our customers to forget the rules and shop unbiasedly," Stockmann chief operating officer Anna Salmi told the Australian site SheSociety.
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NG: Otis and Eric – a lot of the relationships in Sex Education are very sweet but... unbiasedly, one of my favorites is Eric and Otis's, just cause they're so different, but they complement each other so well.
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Washington (CNN)The first Latino attorney general in U.S. history believes Donald Trump has a right to question whether a judge with Hispanic background who is presiding over a Trump University lawsuit is able to adjudicate the case unbiasedly.
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Foer provides a parallel between WWII and the 9/11 attacks to not only show the timelessness of trauma and tragedy – how it affects people unbiasedly, but also how coping with trauma also means to revisit the trauma. It is also important to note the impact of the child narrator on the effectiveness of the theme of trauma. In the novel, Oskar never directly addresses through his narration the trauma he faced. Only through his journey through the city and through his grandparents' letters does he mimic the journey one must take when coping with trauma.
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His major prose essay was Veta Vilakkam which ran to 250 pages. The first bilingual Tamil grammar printed in India is also credited to Beschi. He composed various interlingual dictionaries: Tamil-Latin, Latin-Tamil- Portuguese, and Tamil-French and most importantly the four-way lexicon Tamil- Tamil Catur-Agarati which comprised meanings, synonyms, rhymes, etc.A. Raman This book was not printed before 1824. Although it cannot be assumed that his works were well accepted and appreciated by the Protestants, as Blackburn comments, the rival camp unbiasedly “admired Beschi’s literary skills - they printed one of his grammars and another of his books (Vetiyar Olukkam, A Manual for Catechists) became standard reading for them by the nineteenth century…”.
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Graphic breakdown of stratified random sampling In statistics, stratified randomization is a method of sampling which first stratifies the whole study population into subgroups with same attributes or characteristics, known as strata, then followed by simple random sampling from the stratified groups, where each element within the same subgroup are selected unbiasedly during any stage of the sampling process, randomly and entirely by chance. Stratified randomization is considered a subdivision of stratified sampling, and should be adopted when shared attributes exist partially and vary widely between subgroups of the investigated population, so that they require special considerations or clear distinctions during sampling. This sampling method should be distinguished from cluster sampling, where a simple random sample of several entire clusters is selected to represent the whole population, or stratified systematic sampling, where a systematic sampling is carried out after the stratification process. Stratified random sampling is sometimes also known as "stratified random sampling" or "quota random sampling".
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In mathematics, for example in the study of statistical properties of graphs, a null model is type of random object that matches one specific object in some of its features, or more generally satisfies a collection of constraints, but which is otherwise taken to be an unbiasedly random structure. The null model is used as a term of comparison, to verify whether the object in question displays some non-trivial features (properties that wouldn't be expected on the basis of chance alone or as a consequence of the constraints), such as community structure in graphs. An appropriate null model behaves in accordance with a reasonable null hypothesis for the behavior of the system under investigation. One null model of utility in the study of complex networks is that proposed by Newman and Girvan, consisting of a randomized version of an original graph G, produced through edges being rewired at random, under the constraint that the expected degree of each vertex matches the degree of the vertex in the original graph.
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