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Titlebook: Statistics for Engineers; An Introduction with Hartmut Schiefer,Felix Schiefer Textbook 2021 Springer Fachmedien Wiesbaden GmbH, part of Sp

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Statistical Measurement Data and Production,. Therefore, only the relationships between statistical data and production are presented here. The following dimensions are used to characterize product properties in production processes: arithmetic mean, range, and standard deviation/dispersion. The sixfold value of the dispersion is the producti
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Statistical Tests,Examples of statistical tests in technical fields include comparisons of material deliveries in incoming inspections, machine comparisons with regard to production quality, aging tests, and dynamic damage. The statistical tests discussed here are parameter-bound tests. These include the .-test, the
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Correlation, the relationship between a causative variable and an effect. Furthermore, correlations between causes and effects can be determined. Empirical covariance is suitable as a descriptive quantity between two quantities/variables, although it is dimensional. This disadvantage is eliminated by the correl
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Regression,al description—between these variables. The question of what causes and effects are is generally defined for technical tasks. The functional description of the dependence of a target variable can be performed with one or multiple influencing variables. The influencing variables can also have a recip
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Statistical Design of Experiments (DoE),ter, the general procedure for conducting experiments is discussed, and the various experiment designs are ultimately presented: full factorial experiment designs, Latin squares, fractional factorial experiment designs, factorial experiment designs with a center point, and central composite experiment designs and their properties.
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Statistical Tests, is also different. Performing a statistical test involves establishing hypotheses that are answered with a chosen confidence level. The aforementioned statistical tests are described in more detail with examples.
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