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Statistical Thinking for Industrial Problem Solving

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  • Customizing Graphs

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos)   In this video, you learn how to customize graphics in Graph Builder with the file Process Yield.jmp. You see how to change titles and labels, change axes, add reference lines, customize legends, change colors, and annotate graphs.   This example involves the average monthly yield for two...

    julian julian
    4020 views | 4 replies

  • Using the Prediction Profiler

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos)   In this video, we use the Impurity example and fit a model for the response, Impurity, with three predictors, Temp, Catalyst Conc, and Reaction Time. Then we use the Prediction Profiler to better understand the model coefficients.   Let’s begin by selecting Fit Model from the Analyze men...

    julian julian
    8832 views | 1 replies

  • Calculating Prediction and Tolerance Intervals

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos)   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, ...

    julian julian
    13969 views | 6 replies

  • 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 course is comprised of seven modules. Module 7 covers identifying possible relationships, building predictive models, and deriving value from free-form text. The topics covered in this module are outlined below....

    ruthhummel ruthhummel
    1580 views | 0 replies

  • STIPS Module 6: Design of Experiments

    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 course is comprised of seven modules. Module 6 covers the language of DOE and how to design, conduct, and analyze an experiment in JMP. The topics covered in this module are outlined below. Enroll in this and ot...

    ruthhummel ruthhummel
    2494 views | 0 replies

  • STIPS Module 5: Correlation and Regression

    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 course is comprised of seven modules. Module 5 covers the linear association between pairs of variables and fitting and interpreting linear and logistic regression models. The topics covered in this module are o...

    ruthhummel ruthhummel
    1450 views | 0 replies

  • STIPS Module 4: Decision Making with Data

    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 course is comprised of seven modules. Module 4 covers drawing inferences from data, constructing statistical intervals, performing hypothesis tests, and the relationship between sample size and power. The topics...

    ruthhummel ruthhummel
    969 views | 0 replies

  • STIPS Module 3: Quality Methods

    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 course is comprised of seven modules. Module 3 covers tools to quantify, control, and reduce variation in your product, service, or process. The topics covered in this module are outlined below. Enroll in this a...

    ruthhummel ruthhummel
    1063 views | 0 replies

  • STIPS Module 2: Exploratory Data Analysis

    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 course is comprised of seven modules. Module 2 covers describing data with graphics and using interactive visualizations to find and communicate the story in the data. The topics covered in this module are outli...

    ruthhummel ruthhummel
    1730 views | 0 replies

  • STIPS Module 1: Statistical Thinking and Problem Solving

    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 course is comprised of seven modules. Module 1 covers mapping a problem, defining and scoping your project, and determining the data you need to solve your problem. The topics covered in this module are outlined...

    ruthhummel ruthhummel
    2553 views | 0 replies

  • Optimizing Multiple Responses

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos)   In this video, we show how to analyze an experiment with multiple responses, and how to optimize multiple responses, using the file Anodize.jmp.   In this example, a 12-run custom design with five factors was conducted. The experimental objective is to find settings of the factors to opt...

    julian julian
    4813 views | 1 replies

  • Statistical Thinking for Industrial Problem Solving Course

    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 comprised of seven modules, totaling about 30 hours of self-paced learning. Each module includes short instructional videos, JMP demonstrations, questions and exercises. Learn more and enroll at jmp.com/statis...

    ruthhummel ruthhummel
    3443 views | 0 replies

  • Conducting a Gauge R&R Analysis

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos)   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...

    julian julian
    44965 views | 9 replies

  • Creating Comparative Box Plots with Graph Builder

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

      (view in My Videos) In this video, we show how to create side-by-side, comparative box plots for the Impurity data using Graph Builder. We use these box plots to compare the Impurity values for the different reactors and shifts.   First, we select Graph Builder from the Graph menu.   We drag Impurity to the...

    julian julian
    11157 views | 2 replies

  • Binning Data Using Conditional IF-THEN Statements

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos)   In this video, you learn how to create an IF-THEN formula to bin continuous data using the file Measles.jmp.   This data table includes data on the incidence of measles in the United States from 1928 to 2011. In this scenario, we want to create a new variable that groups data into three ...

    julian julian
    8460 views | 1 replies

  • Analyzing an MSA, EMP Method

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos)   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...

    julian julian
    3058 views | 1 replies

  • Creating Bubble Plots

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos)   In this video, we show how to create bubble plots using the Mobile Cellular data. This is data about mobile cell phone subscriptions per 100 people, from 1990 to 2017.   A bubble plot is like a scatterplot, but you can add animations and extra dimensions.   We are interested in exploring...

    julian julian
    3218 views | 1 replies

  • Fitting a Penalized Regression (Lasso) Model

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos) In this video, we show how to fit a penalized regression model using generalized regression in JMP Pro. We use the file Bodyfat 07.jmp and fit a model for %Fat using the Lasso with validation.   First, we fit a linear regression model for %Fat.   To do this, we select Fit Model from the An...

    julian julian
    6874 views | 1 replies

  • Predictive Modeling

    Follow the guided examples in these videos to learn how to:   Create a Validation Column (JMP Pro)Fit a Multiple Linear Regression Model with ValidationFit a Logistic Model with ValidationChange the Cutoff for ClassificationCreate a Classification TreeFit a Regression TreeFit a Decision Tree with ValidationSelect variables using Bootstrap ForestFit a Neural NetworkFit a Neural Model with Two Layer...

    julian julian
    1805 views | 0 replies

  • Visualizing and Exploring Text Data

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos) In this video, you learn how to visualize and explore unstructured text data using the file Pet Owner.jmp.   To analyze these data, we select Text Explorer from the Analyze menu in JMP.   We select Survey Response as the text column, and click OK to run the analysis using the default token...

    julian julian
    4684 views | 0 replies

  • Comparing and Selecting Predictive Models

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos) In this video, we show how to compare and select predictive models in JMP Pro. We use the data set Bodyfat 07 to fit predictive models for continuous %Fat using all of the available predictors.   The column Validation 2 partitions the data into training, validation, and test sets.   We hav...

    julian julian
    5274 views | 0 replies

  • Processing Unstructured Text Data

    In this article, you learn how to process unstructured text data using the file Pet Owner.jmp. This example is based on the file Pet Survey.jmp, in the JMP sample data library.

    julian julian
    2364 views | 0 replies

  • Variable Selection in Generalized Regression

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos) In this video, we use the Chemical Manufacturing data. We fit a logistic regression model for the categorical response, Performance, using generalized regression. Then we show how to do variable selection to reduce this model.   First, we select Fit Model from the Analyze menu. We select P...

    julian julian
    2199 views | 0 replies

  • Fitting a Linear Model in Generalized Regression

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos) In this video, we show how to fit linear models using generalized regression. We use the Chemical Manufacturing data and fit a least squares model for the continuous response, Yield. Then we fit a logistic regression model for the categorical response, Performance.   First, we fit a linear...

    julian julian
    2793 views | 0 replies

  • Fitting a Neural Model with Two Layers

    Learn more in our free online course:
    Statistical Thinking for Industrial Problem Solving

    (view in My Videos)   In this example, we use the Chemical Manufacturing 2 data. We fit a neural network model for the categorical response, Performance, using all of the available predictors and the validation column. We use the options available in JMP Pro for this demo.   First, we select Analyze, then Pre...

    julian julian
    1837 views | 0 replies