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JMP Academic Webinar - JMP 101: Teaching Statistics with JMP
Thursday, January 20, 2022
Post questions or comments below. The JMP Journal from the presentation is available for download in the Attachments section to the right. Are you a statistics instructor who's new to 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. We'll explain the JMP interface and demonstrate data importing, data summarization and graphing, foundational analyses such as regression and ANOVA, and saving and exporting your work. Along the way, we'll highlight some tips for teaching with JMP and will briefly review our collection of free teaching tools and resources. Find additional teaching and learning resources at www.jmp.com/academic.
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JMP Academic Webinar - Tools for Data Exploration
Thursday, February 3, 2022
Post questions or comments below. The JMP Journal from the presentation is available for download in the Attachments section to the right. 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. Find additional teaching and learning resources at www.jmp.com/academic.
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Academic Webinar
Data Exploration and Visualization
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JMP Academic Webinar - Teaching Categorical Data Analysis
Thursday, February 17, 2022
Post questions or comments below. The JMP Journal from the presentation is available for download in the Attachments section to the right. Categorical data is common across many domains, and concepts and techniques including confidence intervals for proportions, chi square tests, logistic regression, and more are critical in developing students' competence in categorical data analysis and interpretation. JMP includes a range of easy-to-use tools both for analyzing categorical data and for teaching associated statistics concepts. 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. Find additional teaching and learning resources at www.jmp.com/academic.
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Academic Webinar
Basic Data Analysis and Modeling
Data Exploration and Visualization
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JMP®: A Case Study Approach to Data Exploration
Monday, February 28, 2022
The course begins with an introduction to the JMP interface with its key tools and features, followed by two case studies that present common data issues that students encounter. Each case study demonstrates the elements of a typical workflow for data exploration. This course will help you prepare to use JMP in more advanced courses covering statistical analysis and modeling, design of experiments and quality control, or the JMP Scripting Language. Learn how to Import data into JMP. Explore the data with graphs and tables. Identify and correct data problems. Create new columns with formulas. Save and share graphical and numerical reports. Duration: 2 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Data Exploration and Visualization
JMP Education
Sharing and Communicating Results
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JMP®: A Case Study Approach to Data Exploration
Tuesday, March 1, 2022
The course begins with an introduction to the JMP interface with its key tools and features, followed by two case studies that present common data issues that students encounter. Each case study demonstrates the elements of a typical workflow for data exploration. This course will help you prepare to use JMP in more advanced courses covering statistical analysis and modeling, design of experiments and quality control, or the JMP Scripting Language. Learn how to Import data into JMP. Explore the data with graphs and tables. Identify and correct data problems. Create new columns with formulas. Save and share graphical and numerical reports. Duration: 2 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Data Exploration and Visualization
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Sharing and Communicating Results
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JMP Academic Webinar - Teaching Predictive Modeling with JMP
Thursday, March 3, 2022
Post questions or comments below. The data set from the presentation is available for download in the Attachments section to the right. Predictive modeling is a core part of education in data science, business analytics, and other domains. JMP and JMP Pro include machine learning algorithms commonly taught in this area, including decision trees, neural networks, support vector machines, k nearest neighbors, and more, and JMP's interactive, point-and-click interface enables students to learn these methods without writing code. This webinar will demonstrate how to use JMP's predictive modeling tools in the classroom and will highlight free teaching resources available to complement your course. Find additional teaching and learning resources at www.jmp.com/academic.
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Academic Webinar
Predictive Modeling and Machine Learning
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JMP Academic Webinar - Analyzing Functional (aka Curve) Data
Thursday, March 17, 2022
Post questions or comments below. The examples from the presentation are available for download in the Attachments section to the right. 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. Find additional teaching and learning resources at www.jmp.com/academic.
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JMP®: Analyzing and Modeling Multidimensional Data
Tuesday, March 22, 2022
Methods for unsupervised learning are presented in which relationships between the observations, as well as relationships between the variables, are uncovered. The course also demonstrates various ways of performing supervised learning where the relationships among both the output variables and the input variables are considered. In the course, emphasis is on understanding the results of the analysis and presenting conclusions with graphs. Learn how to Use principal component analysis to reduce the number of data dimensions Use loading plots to understand the relationships between variables Interpret principal component scores and perform factor analysis Build more stable models by removing collinearity with principal component regression (PCR) Identify natural groupings in the data via cluster analysis Identify clusters of variables Classify observations into groups with discriminant analysis Fit complex multivariate predictive models with partial least squares (PLS) regression models. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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JMP®: Analyzing and Modeling Multidimensional Data
Wednesday, March 23, 2022
Methods for unsupervised learning are presented in which relationships between the observations, as well as relationships between the variables, are uncovered. The course also demonstrates various ways of performing supervised learning where the relationships among both the output variables and the input variables are considered. In the course, emphasis is on understanding the results of the analysis and presenting conclusions with graphs. Learn how to Use principal component analysis to reduce the number of data dimensions Use loading plots to understand the relationships between variables Interpret principal component scores and perform factor analysis Build more stable models by removing collinearity with principal component regression (PCR) Identify natural groupings in the data via cluster analysis Identify clusters of variables Classify observations into groups with discriminant analysis Fit complex multivariate predictive models with partial least squares (PLS) regression models. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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JMP®: Analyzing and Modeling Multidimensional Data
Thursday, March 24, 2022
Methods for unsupervised learning are presented in which relationships between the observations, as well as relationships between the variables, are uncovered. The course also demonstrates various ways of performing supervised learning where the relationships among both the output variables and the input variables are considered. In the course, emphasis is on understanding the results of the analysis and presenting conclusions with graphs. Learn how to Use principal component analysis to reduce the number of data dimensions Use loading plots to understand the relationships between variables Interpret principal component scores and perform factor analysis Build more stable models by removing collinearity with principal component regression (PCR) Identify natural groupings in the data via cluster analysis Identify clusters of variables Classify observations into groups with discriminant analysis Fit complex multivariate predictive models with partial least squares (PLS) regression models. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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JMP®: Analyzing and Modeling Multidimensional Data
Friday, March 25, 2022
Methods for unsupervised learning are presented in which relationships between the observations, as well as relationships between the variables, are uncovered. The course also demonstrates various ways of performing supervised learning where the relationships among both the output variables and the input variables are considered. In the course, emphasis is on understanding the results of the analysis and presenting conclusions with graphs. Learn how to Use principal component analysis to reduce the number of data dimensions Use loading plots to understand the relationships between variables Interpret principal component scores and perform factor analysis Build more stable models by removing collinearity with principal component regression (PCR) Identify natural groupings in the data via cluster analysis Identify clusters of variables Classify observations into groups with discriminant analysis Fit complex multivariate predictive models with partial least squares (PLS) regression models. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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JMP®: Statistical Decisions Using ANOVA and Regression
Tuesday, April 5, 2022
You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals and hypothesis testing are introduced and applied. The course also covers principles of model building, including model interpretation and addressing violations of statistical assumptions. Capstone practices at the end of the course allow students to apply their knowledge. Learn how to Interpret confidence intervals. Perform hypothesis tests and interpret p-values. Explore relationships with scatterplots and correlation statistics. Compare multiple population means with one-way ANOVA. Use simple linear regression to analyze relationships between continuous variables. Use the general linear model to build models between a continuous response and any number of continuous or categorical predictors. Assess interactions between factors and curvature. Evaluate assumptions of statistical hypothesis testing. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Basic Data Analysis and Modeling
JMP Education
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JMP®: Statistical Decisions Using ANOVA and Regression
Wednesday, April 6, 2022
You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals and hypothesis testing are introduced and applied. The course also covers principles of model building, including model interpretation and addressing violations of statistical assumptions. Capstone practices at the end of the course allow students to apply their knowledge. Learn how to Interpret confidence intervals. Perform hypothesis tests and interpret p-values. Explore relationships with scatterplots and correlation statistics. Compare multiple population means with one-way ANOVA. Use simple linear regression to analyze relationships between continuous variables. Use the general linear model to build models between a continuous response and any number of continuous or categorical predictors. Assess interactions between factors and curvature. Evaluate assumptions of statistical hypothesis testing. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Basic Data Analysis and Modeling
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JMP®: Statistical Decisions Using ANOVA and Regression
Thursday, April 7, 2022
You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals and hypothesis testing are introduced and applied. The course also covers principles of model building, including model interpretation and addressing violations of statistical assumptions. Capstone practices at the end of the course allow students to apply their knowledge. Learn how to Interpret confidence intervals. Perform hypothesis tests and interpret p-values. Explore relationships with scatterplots and correlation statistics. Compare multiple population means with one-way ANOVA. Use simple linear regression to analyze relationships between continuous variables. Use the general linear model to build models between a continuous response and any number of continuous or categorical predictors. Assess interactions between factors and curvature. Evaluate assumptions of statistical hypothesis testing. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Basic Data Analysis and Modeling
JMP Education
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JMP®: Statistical Decisions Using ANOVA and Regression
Friday, April 8, 2022
You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals and hypothesis testing are introduced and applied. The course also covers principles of model building, including model interpretation and addressing violations of statistical assumptions. Capstone practices at the end of the course allow students to apply their knowledge. Learn how to Interpret confidence intervals. Perform hypothesis tests and interpret p-values. Explore relationships with scatterplots and correlation statistics. Compare multiple population means with one-way ANOVA. Use simple linear regression to analyze relationships between continuous variables. Use the general linear model to build models between a continuous response and any number of continuous or categorical predictors. Assess interactions between factors and curvature. Evaluate assumptions of statistical hypothesis testing. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Basic Data Analysis and Modeling
JMP Education
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JMP®: A Case Study Approach to Data Exploration
Tuesday, April 26, 2022
The course begins with an introduction to the JMP interface with its key tools and features, followed by two case studies that present common data issues that students encounter. Each case study demonstrates the elements of a typical workflow for data exploration. This course will help you prepare to use JMP in more advanced courses covering statistical analysis and modeling, design of experiments and quality control, or the JMP Scripting Language. Learn how to Import data into JMP. Explore the data with graphs and tables. Identify and correct data problems. Create new columns with formulas. Save and share graphical and numerical reports. Duration: 2 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Data Exploration and Visualization
JMP Education
Sharing and Communicating Results
2 attendees
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JMP®: Custom Design of Experiments
Tuesday, April 26, 2022
Custom design is an approach to designing experiments that produces optimal designs for the problem you’re trying to solve, whether that’s identifying important effects, or trying to optimize one or more responses. In addition to learning about custom design in JMP, you’ll explore key design concepts including sample size and power, balance, choice of factor ranges, blocking, and design evaluation. This course is for anyone who works in discovery, research, development, and quality assurance or control, as well as Black Belts who are working on Six Sigma projects. Learn how to Use custom design for any experiment. Choose appropriate criteria for optimal design. Effectively and efficiently test factor effects or predict responses. Augment existing experiments to address new questions. Design and analyze experiments with hard-to-change factors. Eliminate noise from nuisance factors. Find the best factor settings to achieve desired response levels. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Design of Experiments
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JMP Academic Webinar - Teaching Analytics in Chemistry and Chemical Engineering with JMP: A Hands-On Introduction
Wednesday, April 27, 2022
Post questions or comments below. The journal from the presentation is available for download in the Attachments section to the right. Webinar Overview Chemistry and chemical engineering curricula often include a range of statistical techniques, from regression to multivariate methods to design of experiments. With the right software, learning these skills can be hands-on and engaging, helping students explore and analyze data without struggling with tedious software or writing code. JMP is interactive, powerful, and easy point-and-click statistics software that is ideal for engaging, hands-on statistics teaching, and it also is used by scientists and engineers at chemical companies across the globe. This webinar will show you how JMP can help engage your students' curiosity and build their analytics skills, all through a series of hands-on demonstrations that allow you to try JMP for yourself. Simply download a free 30-day trial of JMP at www.jmp.com/try before the webinar, and then during the webinar the presenters will provide you with sample data sets and lead you through several example analyses. (Of course, you're welcome to simply observe the demonstration if you prefer.) The goal is to help you feel for yourself whether JMP is the right tool for your course. Register now, download and install the free trial at www.jmp.com/try before the webinar, and then join us on April 27 th for a hands-on introduction to JMP. Helpful Links Free 30-day trial: www.jmp.com/try JMP Academic Program: www.jmp.com/academic Free Teaching materials: www.jmp.com/teach JMP use in chemical industry: https://www.jmp.com/en_us/customer-stories.html#by-industrychemical Contact the JMP Academic Team at academic@jmp.com.
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Academic Webinar
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JMP®: A Case Study Approach to Data Exploration
Wednesday, April 27, 2022
The course begins with an introduction to the JMP interface with its key tools and features, followed by two case studies that present common data issues that students encounter. Each case study demonstrates the elements of a typical workflow for data exploration. This course will help you prepare to use JMP in more advanced courses covering statistical analysis and modeling, design of experiments and quality control, or the JMP Scripting Language. Learn how to Import data into JMP. Explore the data with graphs and tables. Identify and correct data problems. Create new columns with formulas. Save and share graphical and numerical reports. Duration: 2 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Data Exploration and Visualization
JMP Education
Sharing and Communicating Results
0 attendees
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JMP®: Custom Design of Experiments
Wednesday, April 27, 2022
Custom design is an approach to designing experiments that produces optimal designs for the problem you’re trying to solve, whether that’s identifying important effects, or trying to optimize one or more responses. In addition to learning about custom design in JMP, you’ll explore key design concepts including sample size and power, balance, choice of factor ranges, blocking, and design evaluation. This course is for anyone who works in discovery, research, development, and quality assurance or control, as well as Black Belts who are working on Six Sigma projects. Learn how to Use custom design for any experiment. Choose appropriate criteria for optimal design. Effectively and efficiently test factor effects or predict responses. Augment existing experiments to address new questions. Design and analyze experiments with hard-to-change factors. Eliminate noise from nuisance factors. Find the best factor settings to achieve desired response levels. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Design of Experiments
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JMP®: Custom Design of Experiments
Thursday, April 28, 2022
Custom design is an approach to designing experiments that produces optimal designs for the problem you’re trying to solve, whether that’s identifying important effects, or trying to optimize one or more responses. In addition to learning about custom design in JMP, you’ll explore key design concepts including sample size and power, balance, choice of factor ranges, blocking, and design evaluation. This course is for anyone who works in discovery, research, development, and quality assurance or control, as well as Black Belts who are working on Six Sigma projects. Learn how to Use custom design for any experiment. Choose appropriate criteria for optimal design. Effectively and efficiently test factor effects or predict responses. Augment existing experiments to address new questions. Design and analyze experiments with hard-to-change factors. Eliminate noise from nuisance factors. Find the best factor settings to achieve desired response levels. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Design of Experiments
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JMP®: Custom Design of Experiments
Friday, April 29, 2022
Custom design is an approach to designing experiments that produces optimal designs for the problem you’re trying to solve, whether that’s identifying important effects, or trying to optimize one or more responses. In addition to learning about custom design in JMP, you’ll explore key design concepts including sample size and power, balance, choice of factor ranges, blocking, and design evaluation. This course is for anyone who works in discovery, research, development, and quality assurance or control, as well as Black Belts who are working on Six Sigma projects. Learn how to Use custom design for any experiment. Choose appropriate criteria for optimal design. Effectively and efficiently test factor effects or predict responses. Augment existing experiments to address new questions. Design and analyze experiments with hard-to-change factors. Eliminate noise from nuisance factors. Find the best factor settings to achieve desired response levels. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Design of Experiments
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JMP®: Statistical Decisions Using ANOVA and Regression
Tuesday, June 7, 2022
You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals and hypothesis testing are introduced and applied. The course also covers principles of model building, including model interpretation and addressing violations of statistical assumptions. Capstone practices at the end of the course allow students to apply their knowledge. Learn how to Interpret confidence intervals. Perform hypothesis tests and interpret p-values. Explore relationships with scatterplots and correlation statistics. Compare multiple population means with one-way ANOVA. Use simple linear regression to analyze relationships between continuous variables. Use the general linear model to build models between a continuous response and any number of continuous or categorical predictors. Assess interactions between factors and curvature. Evaluate assumptions of statistical hypothesis testing. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Basic Data Analysis and Modeling
JMP Education
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JMP®: Statistical Decisions Using ANOVA and Regression
Wednesday, June 8, 2022
You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals and hypothesis testing are introduced and applied. The course also covers principles of model building, including model interpretation and addressing violations of statistical assumptions. Capstone practices at the end of the course allow students to apply their knowledge. Learn how to Interpret confidence intervals. Perform hypothesis tests and interpret p-values. Explore relationships with scatterplots and correlation statistics. Compare multiple population means with one-way ANOVA. Use simple linear regression to analyze relationships between continuous variables. Use the general linear model to build models between a continuous response and any number of continuous or categorical predictors. Assess interactions between factors and curvature. Evaluate assumptions of statistical hypothesis testing. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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JMP Education
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JMP®: Statistical Decisions Using ANOVA and Regression
Thursday, June 9, 2022
You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals and hypothesis testing are introduced and applied. The course also covers principles of model building, including model interpretation and addressing violations of statistical assumptions. Capstone practices at the end of the course allow students to apply their knowledge. Learn how to Interpret confidence intervals. Perform hypothesis tests and interpret p-values. Explore relationships with scatterplots and correlation statistics. Compare multiple population means with one-way ANOVA. Use simple linear regression to analyze relationships between continuous variables. Use the general linear model to build models between a continuous response and any number of continuous or categorical predictors. Assess interactions between factors and curvature. Evaluate assumptions of statistical hypothesis testing. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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JMP®: Statistical Decisions Using ANOVA and Regression
Friday, June 10, 2022
You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals and hypothesis testing are introduced and applied. The course also covers principles of model building, including model interpretation and addressing violations of statistical assumptions. Capstone practices at the end of the course allow students to apply their knowledge. Learn how to Interpret confidence intervals. Perform hypothesis tests and interpret p-values. Explore relationships with scatterplots and correlation statistics. Compare multiple population means with one-way ANOVA. Use simple linear regression to analyze relationships between continuous variables. Use the general linear model to build models between a continuous response and any number of continuous or categorical predictors. Assess interactions between factors and curvature. Evaluate assumptions of statistical hypothesis testing. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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JMP Academic Webinar - Cleaning and Preparing Data for Analysis
Wednesday, June 15, 2022
Post questions or comments below. Webinar Overview 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. Helpful Links Free 30-day trial: www.jmp.com/try JMP Academic Program: www.jmp.com/academic Free Teaching materials: www.jmp.com/teach Contact the JMP Academic Team at academic@jmp.com.
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Academic Webinar
Data Access
Data Blending and Cleanup
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JMP®: Statistical Process Control
Monday, June 27, 2022
This course teaches you how to set up and maintain a statistical process control system using JMP software. Learn how to Describe variation. Generate and interpret basic quality charts. Generate and interpret control charts for measurement data. Improve control chart performance. Calculate and interpret process capability indices. Monitor many variables at once. Handle data that does not meet assumptions, such as batch processing, correlated data, attribute data, or multivariate data. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Quality and Process Engineering
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JMP®: Statistical Process Control
Tuesday, June 28, 2022
This course teaches you how to set up and maintain a statistical process control system using JMP software. Learn how to Describe variation. Generate and interpret basic quality charts. Generate and interpret control charts for measurement data. Improve control chart performance. Calculate and interpret process capability indices. Monitor many variables at once. Handle data that does not meet assumptions, such as batch processing, correlated data, attribute data, or multivariate data. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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Quality and Process Engineering
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JMP®: Statistical Process Control
Wednesday, June 29, 2022
This course teaches you how to set up and maintain a statistical process control system using JMP software. Learn how to Describe variation. Generate and interpret basic quality charts. Generate and interpret control charts for measurement data. Improve control chart performance. Calculate and interpret process capability indices. Monitor many variables at once. Handle data that does not meet assumptions, such as batch processing, correlated data, attribute data, or multivariate data. Duration: 4 half-day sessions Visit the course overview to learn more and register for an upcoming session.
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