Analyzing and Interpreting Continuous Data Using JMP: A Step-by-Step Guide
Annotation Based on real-world applications, Analyzing and Interpreting Continuous Data Using JMP: A Step-by-Step Guide, written by Jose Ramirez and Brenda Ramirez, combines statistical instructions with a powerful and popular software platform to solve common problems in engineering and science. In the many case studies provided, the authors clearly set up the problem, explain how the data were collected, show the analysis using JMP, interpret the output in a user-friendly way, and then draw conclusions and make recommendations. This step-by-step format enables users new to statistics or JMP to learn as they go, but the book will also be helpful to those with some familiarity with statistics and JMP.
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alternative hypothesis analysis Analyze assumption average compressive strength average performance box plot Cavity cement Chapter click OK column compressive strength conﬁdence interval Control Chart deﬁned deﬂection degrees of freedom descriptive statistics dialog box Difference to detect effective thickness Einstein’s Data estimate example experimental units F-statistic factor levels ﬁeld ﬁrst ﬁt ﬁve furnace Graph histogram homogeneous JMP output JMP table label linear regression model mass spectrometer noise normal distribution normal quantile plot null hypothesis observational unit Ohms one-sample test one-way ANOVA outliers p-value performance variation Phase platform population means prediction interval qualiﬁcation ratio sample size sample size calculator shown in Figure shows signiﬁcance level signiﬁcance test simple linear regression sources of variation speciﬁcation limits standard deviation standard value statistically signiﬁcant Statistics Note Step studentized residuals summary statistics supplier t-statistic test statistic tests of signiﬁcance tolerance interval variable wafer window