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Andy Field (2009) [1] provided an example of a mixed-design ANOVA in which he wants to investigate whether personality or attractiveness is the most important quality for individuals seeking a partner. In his example, there is a speed dating event set up in which there are two sets of what he terms "stooge dates": a set of males and a set of ...
Examples of nested variation or restricted randomization discussed on this page are split-plot and strip-plot designs. The objective of an experiment with this type of sampling plan is generally to reduce the variability due to sites on the wafers and wafers within runs (or batches) in the process.
Blocking evolved over the years, leading to the formalization of randomized block designs and Latin square designs. [1] Today, blocking still plays a pivotal role in experimental design, and in recent years, advancements in statistical software and computational capabilities have allowed researchers to explore more intricate blocking designs.
A recursive partitioning tree showing survival of passengers on the Titanic ("sibsp" is the number of spouses or siblings aboard). The figures under the leaves show the probability of survival and the percentage of observations in the leaf.
A/B testing (also known as bucket testing, split-run testing, or split testing) is a user experience research method. [1] A/B tests consist of a randomized experiment that usually involves two variants (A and B), [ 2 ] [ 3 ] [ 4 ] although the concept can be also extended to multiple variants of the same variable.
For example, nested tables (tables inside tables) should be separated into distinct tables when possible. Here is a more advanced example, showing some more options available for making up tables. Users can play with these settings in their own table to see what effect they have.
The full table of signs for a three-factor, two-level design is given to the right. Both the factors (columns) and the treatment combinations (rows) are written in Yates' order. The value of arranging the sum in Yates' order is now apparent, as only the signs need to be altered according to the table to produce the effect estimates for every ...
The results of that example may be used to simulate a fractional factorial experiment using a half-fraction of the original 2 4 = 16 run design. The table shows the 2 4-1 = 8 run half-fraction experiment design and the resulting filtration rate, extracted from the table for the full 16 run factorial experiment.