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Example of direct replication and conceptual replication. There are two main types of replication in statistics. First, there is a type called “exact replication” (also called "direct replication"), which involves repeating the study as closely as possible to the original to see whether the original results can be precisely reproduced. [3]
Balanced repeated replication is a statistical technique for estimating the sampling variability of a statistic obtained by stratified sampling. Outline of the technique [ edit ]
Pseudoreplication due to correlation of samples: without accounting for correlation the 90% confidence interval for the sample mean is much too small. To get around this problem for example the blocking method can be applied where correlated samples are first grouped, then the (for each block) the corresponding sample means are computed. From ...
For example, if there are 3 levels of the primary factor with each level to be run 2 times, then there are 6! (where ! denotes factorial) possible run sequences (or ways to order the experimental trials). Because of the replication, the number of unique orderings is 90 (since 90 = 6!/(2!*2!*2!)). An example of an unrandomized design would be to ...
However, certain conditions must be met before the replication of the experiment is commenced: the original research question has been published in a peer-reviewed journal or widely cited, the researcher is independent of the original experiment, the researcher must first try to replicate the original findings using the original data, and the ...
Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method.For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated.
For example, a child who has a profound deficiency in growth hormone (especially if they are a cancer survivor with damage to the pituitary gland) may need to continue taking HGH as an adult, ...
The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power. In complex studies ...