Titlebook: Engineering Statistics; An Introduction Edward B. Magrab Textbook 2022 The Editor(s) (if applicable) and The Author(s), under exclusive lic

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書目名稱Engineering Statistics影響因子(影響力)




書目名稱Engineering Statistics影響因子(影響力)學(xué)科排名




書目名稱Engineering Statistics網(wǎng)絡(luò)公開度




書目名稱Engineering Statistics網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Engineering Statistics被引頻次




書目名稱Engineering Statistics被引頻次學(xué)科排名




書目名稱Engineering Statistics年度引用




書目名稱Engineering Statistics年度引用學(xué)科排名




書目名稱Engineering Statistics讀者反饋




書目名稱Engineering Statistics讀者反饋學(xué)科排名

歹徒

高調(diào)

Hay-Fever

https://doi.org/10.1007/978-3-319-44579-3xperiment, and a 2.-factorial experiment are derived. For these experiments, an analysis of variance is used to determine the factors that are most influential in determining its output and, where appropriate, whether the factors interact.

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GLOOM

GLOOM

The United Nations Alternative,s why it is necessary to plot data before attempting to model it, state general guidelines and limits of a straight-line model to data, and show how one determines whether plotted data that appear to be nonlinear could be intrinsically linear. Hypothesis tests are introduced to determine which parameters in the model are the most influential.

不容置疑

Textbook 2022likely to use: the display of data, confidence intervals, hypothesis testing, fitting straight lines to data, and designing experiments to find the impact of process changes on a system or its output. It introduces the language of statistics, derives equations with sufficient detail so that there is

嚙齒動(dòng)物

Continuous Probability Distributions, Confidence Intervals, and Hypothesis Testing,duced and the type I and type II errors are defined. The use of operating characteristic (OC) curves to determine the magnitude of these errors is illustrated. Also introduced is a procedure to obtain probability plots for the normal distribution as a visual means to confirm the normality assumption for data.

insincerity

Regression Analysis and the Analysis of Variance,s why it is necessary to plot data before attempting to model it, state general guidelines and limits of a straight-line model to data, and show how one determines whether plotted data that appear to be nonlinear could be intrinsically linear. Hypothesis tests are introduced to determine which parameters in the model are the most influential.