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Academic Webinar Library

The JMP Global Academic Program provides live webinars each semester for faculty and students wanting to learn about JMP. Below you will find recorded versions of our most recent webinar for each topic in the series. 

To sign up for an upcoming live webinar, please visit our Live Academic Web Series page.

 

Teach with JMP

JMP 101: Intro to JMP for Teachers

Are you new to teaching with JMP and wondering, "Where do I start?" Or perhaps you've taught with JMP before but could use a refresher on the fundamentals. Either way, this webinar aims to give you the foundational knowledge you need to use JMP effectively in your teaching. You'll learn how to: navigate the JMP interface; import, visualize, and analyze data; and save and share results. You'll also learn about JMP's free teaching resources, including sample data sets, case studies, instructional videos, and interactive teaching applets.

Teaching Univariate Statistics and Probability with JMP

Univariate statistics and probability form a foundation for understanding many further statistical concepts. This webinar provides the knowledge you need to teach this foundational topic with JMP. We demonstrate tools for performing univariate analyses of both categorical and continuous data. We also will review a suite of interactive teaching tools to help your students understand fundamental statistical concepts such as Sampling Distributions, Confidence Intervals, Hypothesis Testing, p-values, and Power, among others.

Teaching ANOVA and Regression with JMP

In this webinar, we will explore platforms in JMP made for carrying out ANOVA and Regression analyses, as well as interactive teaching and learning tools to explore concepts related to ANOVA and Regression.

Teaching Categorical Data Analysis with JMP

JMP includes a range tools that are helpful in teaching categorical data analysis concepts and techniques, including confidence intervals and hypothesis tests on proportions, contingency analyses, logistic regression, and more. This webinar will provide an overview of these tools along with some teaching-oriented tips along the way, and it will also provide a brief review of JMP's free teaching resources related to categorical data analysis. By the end, you'll be better prepared to use JMP to teach categorical data analysis in your course.

Teaching Predictive Modeling with JMP Pro

In this webinar we show how to teach the tools and techniques commonly used by academics in business schools and analytics programs, including multiple linear and logistic regression, classification and regression trees, advanced tree methods, neural networks, model validation, and model comparison and selection.  We also introduce new predictive modeling features in JMP 13 Pro, including Formula Depot and Text Explorer.

November 7th and 9th, 2017. Presented by: Mia Stephens

 

Teaching Clustering with JMP

This webinar demonstrates the many resources and tools available in JMP to help you incorporate cluster analysis into your curriculum. We review JMP's clustering tools, which include k-means, hierarchical clustering, and more, as well as how to use these tools effectively for teaching. We also see how the interactive and graphical nature of JMP can help your students develop strong conceptual understandings of this powerful technique.

Teaching Mixed Models with JMP and JMP Pro

Mixed models — models with both fixed and random effects — have become mainstream in many disciplines. This webinar features Elizabeth Claassen, JMP developer and co-author of the book JMP for Mixed Models, providing an overview of mixed models in JMP as well as several examples from the book that may be useful in teaching this advanced topic.

Teaching Generalized Linear Mixed Models with JMP Pro

Generalized Linear Mixed Models (GLMMs) are commonly taught in advanced regression courses and in specific application areas where it is necessary to model non-normal responses as a function of both fixed and random factors. JMP Pro 17 includes new GLMM capabilities that bring JMP Pro's interactive, no-code interface to this powerful modeling technique. This webinar demonstrates how to use JMP Pro 17's GLMM capabilities through examples suitable for classroom use.

Teaching Text Mining Without Writing Code

Text Explorer enables students to learn basic and advanced text mining methods through JMP's interactive point-and-click interface, making text mining more accessible to a wider range of students and disciplines. This webinar demonstrates text mining techniques including word clouds, latent semantic analysis, topic analysis, and sentiment analysis. If you'd like to incorporate text mining into your course but don't want to teach coding, this webinar shows you how.

Teaching Statistical Quality Control with JMP

This webinar demonstrates the many resources and tools available in JMP to help you teach statistical quality control methods. We review JMP’s interactive control chart, process capability analysis, and measurement systems analysis tools and how to use them effectively for teaching. We also review JMP's free teaching resources related to statistical quality control that you can use to complement your course.

Making Hypothesis Testing More Intuitive for Our Students

Hypothesis testing is a particularly challenging topic for many students. This webinar demonstrates interactive graphics and simulations that can help make concepts such as p-values, alpha, and power more intuitive for our students, and as a result help them become competent hypothesis testing practicioners.

Teaching Design of Experiments

In this webinar we demonstrate JMP tools and resources to make teaching DOE most effective. 

Sept 10th, 2020. Presented by: Volker Kraft

Resources for Teaching Statistics with JMP

In this webinar, we step through our collection of teaching and learning resources. These include applets to illustrate statistical concepts, brief video and PDF guides to show your students how to use JMP (so you don't have to), case studies and exercises for in-class or homework activities, and more. Use these resources to complement your course or lighten your load.

Resources for Teaching Engineering Statistics

In this webinar, we identify resources, specific to an engineering statistics or DOE course, that you can use to help teach concepts, provide examples and instructional videos, to teach JMP software skills, and to support student learning. Resources include examples, assignments, or instructional videos, interactive concept demos, case studies, eLearning courses with certificates of completion, and other instructional or supplementary materials.

Watch this alone, or supplement it with additional resources from the first webinar of this series, “Resources for Teaching Intro Stats.”

July 21st, 2020. Presented by: Volker Kraft

Resources for Teaching Business Statistics

In this webinar, we identify resources, specific to a Business Statistics or Analytics course, that you can use to help teach concepts, provide examples and instructional videos, to teach JMP software skills, and to support student learning. Resources include examples, assignments, or instructional videos, interactive concept demos, case studies, eLearning courses with certificates of completion, and other instructional or supplementary materials.

Watch this alone, or supplement it with additional resources from the first webinar of this series, “Resources for Teaching Intro Stats.”

Aug 4th, 2020. Presented by: Kevin Potcner

Using the JMP Statistical Concept Applets

In this webinar we demonstrate the Built-in applets in JMP:

1. Distribution Calculator — calculate critical values and p-values in various distributions
2. Distribution Generator — build discrete distributions and explore PDF and CDF
3. Sampling Distribution of Sample Means
4. Sampling Distribution of Sample Proportion
5. Confidence Interval for the Population Mean
6. Confidence Interval for the Population Proportion
7. ***I skipped the Hypothesis Test for Mean and the Hypothesis Test for Population Proportion, but you can get the idea from the other applets, and use the Help documentation for more help!***
8. Demonstrate Regression
9. Demonstrate ANOVA
10. Additional Resources: Demonstrate P-Value
11. Additional Resources: Permutation Test for Two Means or Medians
12. ***I skipped the Additional Resources options for Demonstrate Power, Bayes Rule, and Collinearity. Use the Help documentation for more help!***

Nov 26th, 2018. Presented by: Ruth Hummel

JMP for Grading and Assessment

The JMP for Grading and Assessment webinar introduces features of JMP useful for managing student grades in courses. You will learn how to: Import and export student grades to campus CMS systems, check grades for entry errors, create weighted averages across assignments, create standardized scores for assignments, create score columns dropping a lowest score, and how to generate letter grades based on scoring criteria.

Research with JMP

Cleaning and Preparing Data for Analysis

Researchers are intimately familiar with the amount of work often needed to clean and prepare data so it’s ready to perform specific statistical analyses. At times, these efforts can take quite a bit more time than the analyses themselves. In this webinar, a statistical scientist from JMP demonstrates a variety of easy-to-use tools to help expedite these efforts. Topics include importing data, recoding and transforming variables, filtering data, and recording/automating operations, among others.

Tools for Data Exploration

Each new data set we encounter brings with it the need for initial data exploration. Before building models or running tests, we need to summarize the data numerically and graphically, screen for patterns or anomalies, and ensure that the data are suitable for further analysis. Put more generally, we need to "get to know" our data. In this webinar, you’ll learn JMP tools and techniques you can use for  the initial exploration of every new data set you analyze.

Data Summary and Analysis

This webinar reviews methods of summarizing and graphing data in JMP, including tables, box plots, scatterplots, and geographic maps.  We also cover analyses for univariate and bivariate data (ANOVA, regressions, logistic regression, and contingency tables) and extending these to multiple predictor models. Finally, we briefly cover multivariate summary (correlations) and clustering, plus creating word clouds to summarize text data. 

  • Who should watch? 
    Any student, researcher or faculty member interested in using JMP for data summarization and/or analysis.
  • What can I expect to get out of the webinar? 
    You will learn how to conduct univariate, bivariate, and multivariate data summarization and analysis in JMP.

November 13th, 2017.  Presented by: Ruth Hummel

Visualization and Graphics

Overview of graphing in JMP using the Graph Builder. Topics include: using drop zones, graph types and controls, creating custom error bars, graph customizations, and exporting graphics for publication or sharing on the web.

JMP features demonstrated:

Graph > Graph Builder

Data Preparation and Modeling

In this webinar we explore several platforms in JMP that make data preparation quick and easy. Then, we show how to build predictive models in JMP Pro. The emphasis is on tools and techniques commonly used by academics in business schools and analytics programs, including multiple linear and logistic regression, classification and regression trees, advanced tree methods, neural networks, model validation, and model comparison and selection.

Data Visualization and Modeling

Data Visualization and Modeling will show how to construct interactive data visualizations and predictive models in JMP Pro. The emphasis will be on tools and techniques commonly used by students and faculty in business schools and analytics programs, including dynamic graphics, multiple linear and logistic regression, classification and regression trees, advanced tree methods, neural networks, model validation, and model comparison and selection.

Building, Diagnosing, and Interpreting Linear Regression Models

Linear regression modeling is one of the most widely used statistical tools in academic research. Applying this foundational technique effectively requires a degree of technical knowledge regarding model construction, diagnostics, and interpretation. This webinar, which is appropriate for novice to intermediate linear modelers, will help you build the technical knowledge to be able to confidently use linear regression models in your work. We'll see how to: build standard least squares regression models with a mix of continuous and categorical factors, diagnose and address common problems with regression models, and interpret model parameters appropriately.

Statistical Analyses for Comparison Research Studies

Many research studies involve testing for and quantifying the differences between treatments. These studies could consist of a simple A/B comparisons of a single factor all the way to exploring the impact that multiple factors including their potential interactions have on an outcome. In this webinar, a statistical scientist from JMP demonstrates a variety of tools in JMP that researchers can use to design comparative studies and perform the proper analyses needed to determine if there are statistical differences across treatments.

Research Methods with JMP: Clustering, Factor Analysis, and SEM

In this webinar we will explore techniques needed for Research Methods, including high-dimensional data visualization and modeling using JMP's graphing and multivariate analysis platforms (e.g. Multivariate, Cluster, PCA, Factor Analysis, and SEM).

Using JMP to Analyze Data with Many Variables:

Sept 15th, 2020. Presented by: Kevin Potcner

In the webinar you will learn tools in JMP that can analyze data with a large number of variables. Techniques will include: 1. Using animation-based visualization to explore data over time (using Bubble Plot). 2. Performing a large number of statistical tests simultaneously to find those response variables that result in statistically significant results (using Response Screener). 3. Finding the variables that most impact a response when there are more variables than observations (using Bootstrap Forest). 4. Comparing variation between two groups of highly-dimensional data (using Principal Component Analysis).

Analyzing Functional (aka Curve) Data with JMP Pro

Researchers in numerous domains often encounter functional data, or one continuous measure that unfolds across another. Prominent examples include chemical spectra, financial series, and sensor data; think any data where the unit of analysis is not a single point, but a curve. Functional data analysis (FDA) offers techniques to analyze these curves in order to characterize their shapes and to understand how other variables affects their shapes, how their shape characteristics affect other variables, and even how to optimize their shapes. JMP Pro's Functional Data Explorer  enables researchers to use FDA techniques to solve analytic problems involving this potentially challenging type of data. This webinar will provide an overview of FDA and Functional Data Explorer in order to help you add FDA to your research tool belt.
 

Producing Publication-Quality Graphics

Research publications and presentations call for high-quality data visualizations, often following specific formatting requirements, aesthetic preferences, or other customization needs. While most JMP users are aware of JMP's strength in exploratory graphing, fewer are aware that JMP also is capable of producing highly customized, publication-quality graphs. In this webinar, you'll learn basic and advanced techniques for customizing graph formats and aesthetics as well as how to export graphs in high-quality image formats that can be resized without becoming blurry or pixelated. You'll also see how to perform extremely fine customizations on JMP graphs after exporting them, opening up a nearly infinite level of customization.

The Scientific Workflow in JMP: Creating Reproducible Analyses

In the webinar we will see how to use JMP journals and scripting to keep track of an analysis workflow in a professional research environment. Our attention will be on how to create analyses that are easily reproducible if data were to change, and the documentation of an analysis process for reporting in journals or to professional colleagues.

JMP Integration and Extensibility

In this webinar we explore many ways to extend core JMP functionality through its integration with R and Python. We show how to connect JMP to R and Python, how to create your own add-ins for JMP that take advantage of these connections, and where to find more examples and help on this topic. We also reference the JMP integration with SAS, CAS, and Matlab, and even code-generation in Python, C, SAS, SQL, and Javascript.

This webinar is geared for JMP users who need an analysis available only in R or Python, or users of R and Python who also want to make use of time-saving, interactive, and powerful features in JMP, as well as JMP users who want to package a JMP GUI front-end for an R or Python routine, to allow other JMP users to “use” R and Python in a JMP point-and-click interface. 

JMP for Your Discipline

Teaching Analytics in Chemistry

This webinar demonstrates teaching tools and free resources commonly used within Chemistry and Chemical Engineering. An important topic will be Design of Experiments using classical, mixture, functional or flexible custom designs, and how to analyze and understand experimental data. In addition to multivariate methods like Partial Least Squares or Functional Data Analysis, see how to teach quality methods and six sigma in the most visual, interactive and engaging way.  

Jan 7th, 2021. Presented by: Volker Kraft

Teaching Engineering Statistics with JMP

In this webinar we demonstrate tools in JMP to make teaching engineering statistics most effective. 

Oct 11th, 2017. Presented by: Volker Kraft

Teaching Business Analytics and Data Science with JMP

Business analytics and data science are core parts of many business curricula. This webinar begins with a brief interview with a special industry guest, providing some perspective on the use of analytics and JMP Pro at a major investment management firm. It then provides an overview of JMP capabilities and resources for teaching business analytics and data science. It is appropriate both for those considering teaching with JMP and for those who already teach with JMP but would like a refresher on the tools available to them.

Better Teaching (and using) Data Analytics for Materials Science

In this webinar we show university instructors and students best practices to better teach and learn the best data analysis to easily discover, design and manufacture new materials and accelerate materials property calculation using exploratory data analysis, Machine Learning, design of experiments and data modeling.

Jun 19th, 2019. Presented by: Volker Kraft

Teaching Statistics in the Health and Life Sciences

This webinar will show how to teach the tools and techniques commonly used by professors and students in health and life sciences fields, including ANOVA and regression, mixed models, survival analysis, designed experiments, and graphical tools.

December 12th, 2017. Presented by: Ruth Hummel

Biostatistics and Health and Life Sciences in JMP (Basics)

This webinar covers tools commonly used within the health sciences, including interactive graphics, descriptive statistics, fitting distributions, confidence intervals and hypothesis tests, odds ratios, relative risk, linear and logistic regression, and a very brief introduction to survival analysis and fitting mixed models (in JMP and JMP Pro).

Biostatistics and Health and Life Sciences in JMP (Advanced)

This webinar covers how to use the tools and techniques commonly needed by researchers, practitioners, professors, and students in biostatistics and the health and life sciences fields. Topics covered include ANOVA and regression (including variable selection using penalized regression), mixed models (including split-plot or heirarchical and repeated measures), survival analysis, and designing an experiment in JMP.

April 12th, 2018. Presented by: Ruth Hummel

JMP for Institutional Research

JMP for Institutional Research webinars will demonstrate a variety of analysis tools and platforms in JMP useful for analyzing data commonly used by professionals in Academic Institutional Research.

Special Editions

New in JMP 17 and JMP Pro 17 for Academics

JMP 17 and JMP Pro 17 were released in October 2022 with many new features useful to statistics teachers and academic researchers. This webinar provides and overview of a selection of new features, including:

Workflow Builder, a point-and-click tool for creating documented, reproducible analysis workflows

JMP Search for finding and launching the specific analysis you need

Generalized Linear Mixed Models for building linear models with both random effects and non-normal response distributions

Easy DOE, a new design of experiments platform that guides users step-by-step through the design and analysis of an experiment

– Improvements to the Structural Equation Models and Sample Size Explorers platforms

Modern Design of Experiments

Special Guests:
Bradley Jones, PhD, Distinguished Research Fellow, JMP Statistical Discovery
Douglas Montgomery, PhD, Regents Professor of Industrial Engineering and Statistics, Arizona State University

In this JMP Academic Series webinar, we are joined by Dr. Bradley Jones and Dr. Douglas Montgomery to learn about their new book "Design of Experiments: A Modern Approach." They describe the need for a modern approach to teaching and using DOE. In the process, they point out the connections between optimal modern designs, orthogonality in designs, and well-known traditional designs.

Statistical Quality Control

Special Guests:
Brenda S. Ramírez, MS, Industrial Statistician and JMP Author
José G. Ramírez, PhD, Industrial Statistician and JMP Author

Ms. Brenda Ramírez and Dr. José Ramírez are long-time practitioners and educators of Statistical Quality Control techniques in the semiconductor, chemical, electronics, and biotechnology industries. This webinar covers examples from their new book, "Douglas Montgomery’s Introduction to Statistical Quality Control: A JMP® Companion." This JMP-focused companion book demonstrates the powerful Statistical Quality Control (SQC) tools found in JMP. Geared toward students and practitioners of SQC who are using these techniques to monitor and improve products and processes, this companion provides step-by-step instructions on how to use JMP to generate the output and solutions found in Montgomery’s book, and we cover several of these examples in this webinar. 

Best Practices for Preparing Students for a Career in Business Analytics/Data Science

Special Guests:
George Recck, MBA, Associate Teaching Professor, Babson College
Kymm Hockman, PhD, Statistical Consultant and Trainer
Roger Hoerl, PhD, Associate Professor of Statistics, Union College
Michael Posner, PhD, Professor of Statistics and Data Science, Villanova University

As the fields of business analytics and data science for business continue to evolve, there is much uncertainty about what business programs should teach.

The panel, hosted by George Recck, discusses:

  • What skills and tool sets are critical for business analytics professionals?
  • How can academia prepare students to perform in this ever-changing environment?

First presented at the Joint Statistical Meetings in August 2020, now offered as a free encore guest session in the JMP Academic Webinar Series and sponsored by the ASA’s Business Analytics SE group.

Recorded Nov 19th, 2020.

Biostatistics

Special Guest:
Trevor Bihl, PhD, Depts. of Pharmacology and Toxicology & Biomedical, Industrial, and Human Factor Engineering, Wright State University

Dr. Bihl is both a research scientist/engineer and an educator who teaches biostatistics, engineering statistics, and programming. In this webinar, Dr. Bihl talks about data wrangling and data analysis methods and examples from his recent book, "Biostatistics Using JMP: A Practical Guide," and he discusses his experience teaching these topics and provides a bit of advice to academics in this field. 

Presented on November 13th, 2018.