Abstract
The analysis of variance (ANOVA) is a classic tool for an identification of discreet factors impact on the measurable output by a specific decomposition on a total variance according to the scheme proposed by R.A Fisher in the 1920s. There are many explicit and implicit assumptions required as a preliminary of ANOVA computations. The ANOVA computations scheme is well known and implemented in many types of software but all estimations are provided with the assumption of a normal and homoscedasticity distribution of the noise disturbing the output. Computation procedures produce a single number output (e.g. F statistics, p-Value) without any analysis of their own dispersion. This paper analyzes the ANOVA output using the bootstrap approach. It seems to be the most convenient as a data-driven procedure. The source raw data are taken from the image analysis conducted during the investigation of the impact of the ceramic layer thickness on the wax pattern assembly of a turbine blade on the (γ+γ’) eutectic in the IN713C superalloy.
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