STIPS Module 7: Predictive Modeling and Text Mining
Statistical Thinking for Industrial Problem Solving (STIPS) is a free, online course available to anyone interested in building practical skills in using data to solve problems better. The ...
Statistical Thinking for Industrial Problem Solving (STIPS) is a free, online course available to anyone interested in building practical skills in using data to solve problems better. The ...
Statistical Thinking for Industrial Problem Solving (STIPS) is a free, online course available to anyone interested in building practical skills in using data to solve problems better. The ...
Statistical Thinking for Industrial Problem Solving (STIPS) is a free, online course available to anyone interested in building practical skills in using data to solve problems better. The ...
Statistical Thinking for Industrial Problem Solving (STIPS) is a free, online course available to anyone interested in building practical skills in using data to solve problems better. The ...
Statistical Thinking for Industrial Problem Solving (STIPS) is a free, online course available to anyone interested in building practical skills in using data to solve problems better. The ...
Statistical Thinking for Industrial Problem Solving (STIPS) is a free, online course available to anyone interested in building practical skills in using data to solve problems better. The ...
Statistical Thinking for Industrial Problem Solving (STIPS) is a free, online course available to anyone interested in building practical skills in using data to solve problems better. The ...
Statistical Thinking for Industrial Problem Solving is a free, online course available to anyone interested in building practical skills in using data to solve problems better. The course is comprise...
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In this video, we show how to create a 3-way control chart for the Vial Fill Weights data using the Control Chart Builder.
A version of this file is available in the Sample Data Library in JMP under the Help menu, within the Quality Control folder.
In this example, we are studying ...
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In this video, we show how to add a phase variable to an X-bar and R chart using the Control Chart Builder.
We’ll use the Metal Parts example to see whether there a difference in Thickness before and after implementing process changes. The target thickness is 40 hundredths of an inch.
...
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In this video, we show how to compute capability indices for the Metal Parts example using the Distribution platform in JMP.
To start, we select Distribution from the Analyze menu.
We select Thickness for Y, Columns, and click OK.
To calculate capability indices, we select Process ...
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In this video, we show how to compute capability indices for the Metal Parts example using the Control Chart Builder.
First, we select Control Chart Builder from the Analyze menu under Quality and Process.
We drag the column Thickness into the Y drop zone. Then we drag and drop Hour ...
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In this video, we show how to compute capability indices for nonnormal data using the Impurity data and the Distribution platform in JMP.
To start, we select Distribution from the Analyze menu.
We select Impurity for Y, Columns, and click OK.
The distribution appears to be right sk...
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In this video, we show how to identify poorly performing processes in JMP using the Semiconductor Capability data, found in the Sample Data library.
This table has 128 process variables grouped together in the columns panel. Each variable has the spec limits saved as a column property....
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To design a measurement system study in JMP, we’ll use a script called Gauge Study Design.jsl. This script is in your course data, and a variation of this script is also available in the File Exchange on the JMP User Community.
We’ll design a study with three inspectors measuring 10 pa...
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For this video, we use the file Micrometer.jmp to demonstrate how to visualize the results of a measurement system analysis in JMP.
We use the Gauge R&R MSA method in the Measurement Systems Analysis platform to create variability charts, we and use the EMP method to create average and...
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For this video, we use the file Micrometer.jmp to demonstrate how to analyze an MSA in JMP.
In this MSA, the measurement system of interest is a hand micrometer, and the quality characteristic is the diameter of metal bearings. The study involves three inspectors measuring 10 parts, wi...
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In this video, we use the file Micrometer.jmp to demonstrate how to conduct a Gauge R&R analysis in JMP.
In this study, the measurement system of interest is a hand micrometer, and the quality characteristic is the diameter of metal bearings. The study involves three inspectors measuri...
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In this video, we use the file Area MSA Exercise Final.jmp to demonstrate how to analyze bias in the Measurement Systems Analysis platform.
In this study, the measurement system of interest is the area of several objects, measured by different inspectors. The true value, or standard, i...
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In this video, we use a simulation to construct confidence intervals at different confidence levels, and we explore what it means to be statistically “confident.”
We use the Confidence Interval for the Population Mean teaching module for illustration. This module is available from the ...
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In this video, you learn how to construct a 90% confidence interval for the mean using the Impurity data.
To do this, we use the Distribution platform from the Analyze menu. We select Impurity as the Y, Column and click OK.
A 95% confidence interval is provided, by default, in the Su...
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In this video, you learn how to construct prediction intervals and tolerance intervals in JMP using the file Diameter 04.jmp. This data set contains diameter measurements for 100 parts, collected in rational subgroups.
First, we create a distribution analysis for Diameter. To do this, ...
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In this video, you learn how to conduct a one-sample t test using the file Diameter Test.jmp. This data set contains diameter measurements for 50 randomly selected parts.
First, we run a distribution analysis for Diameter. To do this, we use the Distribution platform from the Analyze m...
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In this video, you learn how to conduct a two-sample t test using the file Breaking Strength.jmp.
In this scenario, the characteristic of interest is the breaking strength of a part in ksi (kilos per square inch). Parts are typically made using Material 1, but they can also be made usi...
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In this video, we show how to conduct a matched pairs t-test using the file Therm.jmp from the Sample Data Library under the Help menu in JMP.
In this scenario, we compare temperature readings on 20 people, taken with two different types of thermometers. For each person, there are two ...
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In this video, you learn how to compare more than two means using one-way analysis of variance, or ANOVA. For this video, we use the file Michelson 1879.jmp in the course data. In this scenario, we test the null hypothesis that the mean velocity is equal for all five trials against the a...
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In this video, you learn how to use the Sample Size for Confidence Intervals calculator to compute the sample size required to create a confidence interval with a specified margin of error.
This calculator is available from the Help menu in JMP, under Sample Data and then Calculators.
...
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In this video, we use the Power animation to explore the relationship between sample size and power for a one-sample t test using the file Diameter Test.jmp.
First, we conduct a one-sample t test for Diameter. To do this, we use the Distribution platform from the Analyze menu. We selec...
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In this video, you learn how to calculate the sample size for a one-sample t test. To do this, we select Sample Size and Power from the DOE menu under Design Diagnostics.
Sample size and power calculations are available for many situations. We’ll select One Sample Mean.
In this scena...
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In this video, you learn how to calculate the sample size for a two-sample t test and ANOVA. To do this, we select Sample Size and Power from the DOE menu under Design Diagnostics.
To calculate the sample size for a two-sample t test, we select Two Sample Means.
In this scenario, the...
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To explore the impact of unusual observations and outliers on the correlation coefficient, we use the demoCorr script. This script is in the JMP Sample Scripts Directory.
The demo correlation script starts with several observations and allows us to drag points or add new points and exp...
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Correlation is a measure of the linear association between two variables. In this video, we show how to assess correlations for the Cleaning data using three platforms: Graph Builder, Fit Y by X, and Multivariate.
We start with the Graph Builder, which is the first option under the G...
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In this video, we use the Cleaning data to fit a regression model for Removal and OD using Graph Builder and Fit Y by X.
We start with the Graph Builder, which is the first option under the Graph menu.
We'll drag Removal to the Y zone, and then drag OD to the X zone. The default grap...