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Statistical Thinking for Industrial Problem Solving

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  • Fitting a Decision Tree with Validation

    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 example and fit a regression tree for the continuous response, Yield. We use JMP Pro for this demo.   The acceptable yield for this process is 80%.   The data have been partitioned into training and validation data. 60% of the observations...

    julian julian
    5901 views | 0 replies

  • Variable Selection with a Bootstrap Forest

    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 example and fit a bootstrap forest for the continuous response, Yield. We use JMP Pro for this demo.   The acceptable yield for this process is 80%. There are 17 potential predictors, and only 90 observations. We'll use a bootstrap forest ...

    julian julian
    3779 views | 0 replies

  • Fitting a Neural Network

    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 2 data. We fit a neural network model for Yield using the options available in the standard version of JMP for this demo.   First, we select Analyze, then Predictive Modeling, and then Neural.   We start by adding Yield as the Y, Response ...

    julian julian
    4320 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
    2366 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
    3592 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
    2782 views | 0 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
    8304 views | 1 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
    3004 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
    6113 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
    6036 views | 0 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
    2358 views | 0 replies