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布里斯班代写assignment:样本的选择
2018-03-01 16:50
在便利样本中,可以出现任意数量的偏差。通过选择特定人群,比如在社会学101上学的学生,在周六上午10点到下午2点之间参观购物中心的人,或者图书馆的资助人,这项研究无意中排除了大量的人口。只有在某一所大学的特定教室里选择学生,才能很容易地排除一般民众的某些部分,例如儿童或没有经济手段的学生。这样的排除并不总是一个问题。例如,一项关于图书馆读者的研究可以很容易地在某一图书馆中获取人们的便利样本,并归纳出结果。另一方面,一项针对残疾人的社会态度的研究不应该只使用社会学课堂上的学生,因为这并不一定代表了人口的准确横截面。这种无法准确地归纳出这样一个群体的结果,使得它在许多研究中无效。想要得到更有效的结果的研究人员通常会采用“概率样本”,试图得到准确的人口比例。一般来说,研究每个人是不可能的,但可以随机地将人们分配到一项研究中,以保持总体上的人口特征的平衡。例如,进行政治投票的组织通常会试图在一个大的数据库中随机选取对象。这种随机化增加了更精确的池形成的机会,从而产生更好的结果布里斯班代写assignment:样本的选择
Any number of biases can occur in a convenience sample. By selecting from a specific population such as students enrolled in Sociology 101, people visiting a mall between 10:00 am and 2:00 pm on Saturdays, or library patrons, the study inadvertently excludes a great deal of the population. Choosing only students in a particular classroom at a certain university can easily exclude certain portions of the general populace, such as children or those without the financial means to attend the school.Such exclusions are not always a problem. For example, a study on library patrons could easily take a convenience sample of people at a certain library and generalize the results. On the other hand, a study on social attitudes toward people with disabilities should not use only the students in a sociology class, which does not necessarily represent an accurate cross-section of the population. This inability to accurately generalize the results of such a group makes it ineffective for many studies.Researchers who want more valid results typically take a "probability sample," which attempts to get an accurate representation of the population. It is not generally possible to study everyone, but it is possible to randomly assign people to a study with an eye toward retaining a balance of characteristics seen in the population in general. For example, organizations that conduct political polling usually try to draw on a large database of people and select subjects randomly. This randomization increases the chances of a more accurate pool forming to produce results that can be better generalized.
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