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所在平台: Udemy |
课程主页: https://www.udemy.com/course/tabtrainer-minitab-two-way-anova/
课程评论：没有评论
课程名称：Minitab中的双因素方差分析 - 制造业的Tabtrainer培训 课程概述：欢迎参加由Tabtrainer®认证系列提供的专家级培训，这是您在制造业中应用统计建模的可靠平台。在本课程中，您将掌握使用Minitab®进行的双因素方差分析（ANOVA），基于来自Smartboard公司真实生产数据的案例分析。您将分析层压压力和表面粗糙度如何影响滑板甲板生产中的抗拉剪切强度，并学习如何通过Tukey事后检验验证统计结果。从原始数据准备、模型诊断到图形解释和商业优化，本培训将帮助您自信地评估复杂过程。 本课程由Murat Mola教授主讲，他是 TÜV 认证的六西格玛培训师，并且在2023年被评选为德国年度教授。通过本课程的学习，您将将统计知识转化为可执行的生产策略。 课程内容涵盖： - 数据准备：导入原始测试数据、堆叠列块、分配因子名称和格式化响应变量。 - 视觉分析：使用箱线图和主效应图探索初始趋势，识别预测因子之间可能的交互效应。 - 统计建模：利用广义线性模型（GLM）进行双因素ANOVA，解释p值并理解主效应和交互效应的逻辑。 - 模型诊断：通过R平方和残差分析评估模型质量；利用4合1图和Anderson-Darling检验确认残差的正态分布。 - 事后检验：应用Tukey显著性检验识别哪些特定的压力和粗糙度组合导致显著不同的强度结果。 - 商业解释：得出哪些参数设置可以提供最稳定和高的抗拉剪切强度的结论，并基于统计证据推荐优化的生产配置。 培训结束时，学生将能够： - 构建和解释双因素ANOVA模型。 - 理解并区分主效应与交互效应。 - 应用残差诊断评估模型拟合。 - 使用Tukey分组字母和置信区间验证显著因子组合。 - 将统计结果转化为在工业环境中的具体优化策略。 本培训将应用统计与真实制造业相结合，使参与者在复杂的生产过程中做出更好的基于证据的决策。
Welcome to this expert-level training from the Tabtrainer® Certified Series - your trusted platform for applied statistical modeling in manufacturing.In this course, you will master the Two-Way ANOVA with interaction using Minitab®, based on real production data from the Smartboard Company. You'll analyze how laminating pressure and surface roughness influence the tensile shear strength in skateboard deck production - and learn how to validate statistical results with post-hoc tests like Tukey.From raw data preparation and model diagnostics to graphical interpretation and business optimization, this training builds your skills to evaluate complex processes with confidence.Led by Prof. Dr. Murat Mola, TÜV-certified Six Sigma trainer and Professor of the Year 2023 in Germany, this course empowers you to turn statistics into actionable production strategies:In this training unit, students learn how to apply the Two-Way Analysis of Variance (ANOVA) to evaluate the influence of two categorical factors on a continuous response variable, using a realistic industrial quality control scenario.The case study is taken from the lamination process in skateboard deck production at Smartboard Company, where the tensile shear strength of glued maple layers is the central performance indicator. The two experimental factors - laminating pressure and surface roughness - are each examined at three levels, leading to 9 parameter combinations and 270 measured values.Students follow a structured learning process:Data Preparation: Importing raw test data, stacking column blocks, assigning factor names, and formatting the response variable.Visual Analysis: Using boxplots and main effects plots to explore initial trends and identify possible interaction effects between predictors.Statistical Modeling: Performing a two-way ANOVA with interaction terms using the General Linear Model (GLM), interpreting p-values, and understanding the logic behind main effects and interaction effects.Model Diagnostics: Evaluating model quality with R-squared and residual analysis; confirming the normal distribution of residuals with a 4-in-1 plot and the Anderson-Darling test.Post-hoc Testing: Applying the Tukey significance test to identify which specific combinations of pressure and roughness lead to significantly different strength outcomes.Business Interpretation: Drawing conclusions about which parameter settings deliver the most stable and high tensile shear strength, and recommending optimized production configurations based on statistical evidence.By the end of the training, students are able to:Build and interpret a Two-Way ANOVA model.Understand and distinguish between main effects and interaction effects.Apply residual diagnostics to evaluate model fit.Use Tukey grouping letters and confidence intervals to validate significant factor combinations.Translate statistical results into concrete optimization strategies in an industrial environment.This training connects applied statistics with real-world manufacturing and enables participants to make better, evidence-based decisions in complex production processes.
