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.
Teaching with JMP
- JMP 101: Intro to JMP for Teachers
- New in JMP 16 for Teaching
- Teaching Univariate Statistics and Probability with JMP
- Teaching ANOVA and Regression with JMP
- Teaching Categorical Data Analysis with JMP
- Teaching Predictive Modeling with JMP Pro
- Teaching Clustering with JMP
- Teaching Mixed Models with JMP
- Teaching Text Mining Without Writing Code
- Making Hypothesis Testing More Inuitive for our Students
- JMP Student Edition: Data Exploration and Analysis
- Resources for Teaching Statistics with JMP
- Resources for Teaching Engineering Stats
- Resources for Teaching Business Stats
- Using the JMP Statistical Concept Applets
Design of Experiments and Engineering Statistics
- Teaching Analytics in Chemistry
- Modern DOE
(Guest Speakers, Dr. Bradley Jones and Dr. Douglas Montgomery)
- Statistical Quality Control
(Guest Speakers, Ms. Brenda Ramírez and Dr. José Ramírez)
- Engineering Statistics
- Teaching Engineering Statistics
- Teaching Design of Experiments
- Better Teaching (and Using) Materials Science
Health and Life Sciences
Genetics and Genomics with JMP Genomics
- An Overview of JMP Genomics: Expression, GWAS, and Plant Breeding
- Running and Interpreting a Basic Expression Analysis
- Getting Started with JMP Genomics: Overview of Studies, Import, and Workflows
- Getting Started with JMP Genomics: Creating the EDF and Importing SAM and BAM Files
- JMP Genomics: Move or Share Results
- Producing Pubilcation-Quality Graphics
- The Scientific Workflow in JMP: Reproducible Analyses
- JMP Integration and Extensibility: with R, Python, SAS, CAS, and Matlab
- JMP for Grading and Assessment
- JMP for Institutional Research
- Using JMP to Analyze Data with Many Variables
- Generalized Linear Mixed Models in JMP: GLMM Add-In
Teaching 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.
New in JMP 16 for Teaching
In this webinar, we showcase some of the new features added to JMP 16, released in March 2021. These include enhancements to our popular Graph Builder and Prediction Profiler platforms, the addition of Sentiment Analysis to Text Explorer, and new platforms including Time Series Forecast and Model Screening. These new capabilities and platforms are relevant for both introductory and advanced courses, and all follow JMP’s point-and-click interactive approach to data analysis.
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.
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
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 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.
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.
JMP Student Edition: Data Exploration and Analysis
JMP Student Edition is a very inexpensive (and in many cases free) option for students and teachers in Intro and Intermediate Statistics courses. In this webinar we cover using JMP Student Edition for data exploration and analysis. (The topics covered are also in JMP and JMP Pro.) You can request a free instructor copy of JMP Student Edition. Visit the JMP Student Subscription page for more licensing and textbook integration information.
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.”
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!***
Data Exploration and Analysis
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.
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.
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.
Advanced Research Methods
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).
Advanced Research Methods with JMP
With JMP Pro for Academic Research, you get all the sophisticated techniques and advanced analytics available in JMP Pro. For academic researchers, this translates into a greater ability to efficiently extract meaning from complex data and build better-performing models. In this webinar we see how to estimate a priori power for complex designs using the new Simulate facility in JMP Pro 13. We also expore tools for finding outliers, calculating new variables, shaping and restructuring data, as well as analysis methods for multiple comparisons in the context of large ANOVA designs.
Analyzing Functional (aka Curve) Data with JMP Pro
Special Guest Panel
Best Practices for Preparing Students for a Career in Business Analytics/Data Science
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, Babson College, discusses:
- What skills and tool sets business analytics professionals are critical in this environment?
- How can academia can prepare students to be able to perform in this ever-changing environment?
- Kymm Hockman, recently retired from Dow/Dupont
- Roger Hoerl, Associate Professor of Statistics at Union College and a former manager in the Applied Statistics Laboratory at General Electric
- Michael Posner, Associate Professor of Statistics and Director of the Center for Statistics Education at Villanova University
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.
Design of Experiments and Engineering Statistics
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
Dr. Bradley Jones and Dr. Douglas Montgomery
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.
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.
In this webinar we show how to graph and analyze data in JMP, with an emphasis on tools commonly used by academics in engineering and industrial fields, including control charts, measurement systems analysis and designed experiments.
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
Health and Life Sciences
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
Trevor Bihl, Ph.D.
Faculty in the Department of Pharmacology and Toxicology and Adjunct Faculty in the Biomedical, Industrial & Human Factor Engineering Department, 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.
Genetics and Genomics with JMP Genomics
An Overview of JMP Genomics: Expression, GWAS, and Plant Breeding
JMP Genomics is a statistical discovery software package for universities and research organizations that enables statistical geneticists, biologists, bioinformatics experts and statisticians to uncover meaningful patterns in high-throughput genetics, methylation and expression (metabolomic, transcriptomic and proteomic) data. In this webinar we look at three topic areas in genetic and genomic research and see how JMP Genomics speeds up the analysis and discovery process for (1) Expression Analysis, (2) GWAS, and (3) Plant Breeding.
Running and Interpreting a Basic Expression Analysis
This video shows how to set up, run, and interpret a basic expression analysis in JMP Genomics. In this example I use the Basic RNAseq Workflow, which is a pipeline of some simple exploration on the markers and samples (looking at expression distributions for samples, removing "bad" samples, normalizing the samples' expression, exploring correlations and principle variance components) directly into an ANOVA analysis on the log2(expression) to find markers that are statistically significantly differentially expressed. We explore the resulting output as volcano plots (which we can filter further), Venn Diagrams to find markers significant in multiple comparisons, and tables of information about the final set of selected significant markers. This analysis can apply to any kind of continuous data across any kind of biological markers, such as metabolomics, proteomics, or expression.
Getting Started with JMP Genomics: Overview of Studies, Import, and Workflows
In this video we take a tour of the Genomics Started in JMP Genomics software.
Use this Genomics Starter to explore examples, add studies, import data, and use workflows for common analytical processes.
Getting Started with JMP Genomics: Creating the EDF and Importing SAM and BAM Files
Learn to import SAM or BAM files into JMP Genomics, taking raw (but aligned) data files and creating appropriate count data files that can be used in further analyses within JMP Genomics.
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
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 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.
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.
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).
Generalized Linear Mixed Models in JMP: GLMM Add-In
Jan 27, 2021. Presented by: Ruth Hummel
This webinar covers how to use Generalized Linear Mixed Models in JMP using a new JMP Add-In. These models are commonly needed by researchers, practitioners, professors, and students in the life sciences and related fields. Example will cover mixed models with continuous normally distributed data and then with count data (with integer values 0, 1, 2, …), and with proportion data (with the number of successes out of a specified number of trials). We also cover the basics of random effects, the concept of LSMeans, back-transforming estimates and CIs, creating interaction plots on the original data scale, warnings about the interpretation of differences, and the idea of overdispersion and accounting for this in the Poisson distribution with an experimental unit effect. The webinar is divided into five parts.
- Watch the Video: Part 1, covering mixed models, interaction plots, and LSMeans.
- Watch the Video: Part 2, covering the basic statistical details of GLMMs.
- Watch the Video: Part 3, covering where to find the JMP Add-In, how to install a JMP Add-In, and where to find more examples of using this JMP Add-In.
- Watch the Video: Part 4, covering a count example with a Poisson distribution.
- Watch the Video: Part 5, covering a proportion example with a binomial distribution.
- Download the PPT Slides and Datasets
- Download the Add-In and see more examples
Go directly to these topics at these time stamps:
GLMM Part 1: Intro, Experiment, and lots about Mixed Models (24:09 in length)
- Welcome, and reminder of LM, GLM, MM, and GLMM: 0:00
- Agenda: 2:32
- Review of random effects and mixed models: 3:37
- Key difference between a fixed effect and a random effect 7:06
- Summary of Experiment: 9:22
- Showing the personalities in Fit Model 12:12
- Using SLS and Mixed personalities and seeing the same model but some different output options14:02
- Exploring the interaction and the overlay plot for the mixed model 17:54
- Understanding LSMeans 19:19
GLMM Part 2: More about GLMMs (7:04 in length)
- Count data (a Poisson distribution) 0:00
- Details about and examples of GLMMs 2:35
- Model + Distribution + Link 4:40
- Details about REPL estimation
GLMM Part 3: Download and install the Add-In and find more examples (4:18 in length)
- Webpage to download add-in and find more examples 0:00
- Downloading and installing the add-in 1:54
- Credit to the Add-In author, Meichen Dong 3:32
GLMM Part 4: Count example with Poisson distribution and LOTS of Graphing tips (27:40 in length)
- Setting up the Poisson Mixed Model 0:00
- Back-transforming Estimates and CIs 2:52
- Graph Builder for the Interaction Plot (with lots of JMP tips!!) 10:05
- Saving Figures and Output and Data 17:17
- Overdispersion 18:20
- Back-transforming pairwise comparisons 25:38
- Where to find more examples and ask questions 27:08
GLMM Part 5: Proportion example with Binomial Distribution (9:17 in length)
- Introducing the Binomial Scenario 0:00
- Fitting the binomial GLMM 1:39
- Back-transforming Estimates and CIs 4:00
- Interaction Plot 6:46
- Where to find more examples and ask questions 8:39