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.
Getting Started for Academics
JMP tutorials to help new academic users quickly gain proficiency in the core capabilities of JMP
Data Exploration and Analysis
Design of Experiments and Engineering Statistics
- 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
Teaching with JMP - Preparing Your Course with Free JMP Materials
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
Data Exploration and Analysis
JMP Basics for Professors and Students
This webinar is designed to serve as an initial introduction to JMP. It covers basic navigation, JMP menus and data tables, summarizing and graphing data, and resources for getting started.
JMP features demonstrated:
Analyze > Distribution, Rows > Hide and Rows > Exclude, dynamic plot linking, Rows > Data Filter, Analyze > Fit Y by X (Oneway), Analyze > Multivariate Methods > Multivariate, Analyze > Text Explorer, Analyze > Fit Model, and Graph > Graph Builder
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.
Preparing Data for Analysis with JMP
Guest Speaker:
Robert H. Carver, Ph.D.
Professor of Management and Data Science Program Director
Stonehill College
The 2016 GAISE College Report advocates the incorporation of technology, real data, multivariate thinking, and the importance of the full analytic process in college-level statistics courses. It is clear that data management –including acquisition, merging, subsetting, and preparation -- is a key part of the process. Yet it is a challenge for college instructors to add data management to an already-full course. Data management tasks can be daunting for a student, and the prospect of teaching SQL in Intro Stat can appear overwhelming.
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.
Teaching with JMP
Resources for Teaching Statistics with JMP
Are you preparing to update or prepare a new basic statistics or data analysis course? Looking for new examples, assignments, or instructional videos? Looking for interactive concept demos, case studies, eLearning courses with certificates of completion, or other instructional or supplementary materials?
In these webinars, we identify resources that you can use in your statistics and data analysis courses to help teach concepts, to provide examples and instructional videos, to teach JMP software skills, and to support student learning.
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
Teaching Introductory Statistics with JMP
The webinar is designed to serve as an initial introduction to teaching basic statistics with JMP. It covers how to teach basic navigation, JMP menus and data tables, summarizing and graphing data, and resources for getting started.
Apr 27th, 2017. Presented by: Julian Parris
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 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 Basic Predictive Modeling: Watch the Video
- Teaching Advanced Predictive Modeling: Watch the Video
- Download the Webinar Materials
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 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 here. Find more licensing and textbook integration information here.
Nov 26th, 2018. Presented by: Ruth Hummel
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?
Panelists are:
- 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
Modern Design of Experiments
Guest Speakers:
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.
Statistical Quality Control
Guest Speakers:
Brenda S. Ramírez, M.S. and José G. Ramírez, Ph.D.
ZenEos, LLC
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.
Engineering Statistics
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.
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
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
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 Sciences in JMP
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 an introduction to survival analysis and fitting mixed models (in JMP and JMP Pro).
April 2th, 2015. Presented by: Mia Stephens
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
Biostatistics
Guest Speaker:
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.
JMP Genomics: Move or Share Results
When you move or share a folder of JMP Genomics results, the paths will break. This is a short video to show you how to easily fix those paths.
Special Topics
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 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).
JMP for Social Science Research
Overview of tools and analyses useful for research in the social sciences, including tabulating, graphing, ANOVA and regression.