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Statistical Thinking for Industrial Problem Solving, presented by JMP

SAS via Coursera Help

• Course Overview
• In this module you learn about the course and about accessing JMP software in this course.
• Module 1: Statistical Thinking and Problem Solving
• Statistical thinking is about understanding, controlling and reducing process variation. Learn about process maps, problem-solving tools for defining and scoping your project, and understanding the data you need to solve your problem.
• Module 2A: Exploratory Data Analysis, Part 1
• Learn the basics of how to describe data with basic graphics and statistical summaries, and how to explore your data using more advanced visualizations. You’ll also learn some core concepts in probability, which form the foundation of many methods you learn throughout this course.
• Module 2B: Exploratory Data Analysis, Part 2
• Learn how to use interactive visualizations to effectively communicate the story in your data. You'll also learn how to save and share your results, and how to prepare your data for analysis.
• Module 3: Quality Methods
• Learn about tools for quantifying, controlling and reducing variation in your product, service or process. Topics include control charts, process capability and measurement systems analysis.
• Module 4: Decision Making with Data
• Learn about tools used for drawing inferences from data. In this module you learn about statistical intervals and hypothesis tests. You also learn how to calculate sample size and see the relationship between sample size and power.
• Module 5: Correlation and Regression
• Learn how to use scatterplots and correlation to study the linear association between pairs of variables. Then, learn how to fit, evaluate and interpret linear and logistic regression models.
• Module 6: Design of Experiments (DOE)
• In this introduction to statistically designed experiments (DOE), you learn the language of DOE, and see how to design, conduct and analyze an experiment in JMP.
• Module 7: Predictive Modeling and Text Mining
• Learn how to identify possible relationships, build predictive models and derive value from free-form text.
• Review Questions and Case Studies
• In this module you have an opportunity to test your understanding of what you have learned.

Mia Stephens and Ledi Trutna

• united states

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Stats & Data Science Views

Statistical thinking for industrial problem solving.

A web seminar for scientists and engineers in Chemistry, Pharma and Biotech Industries

Deriving insights from data is crucial to drive innovation and improve processes and products in the chemical, pharma and biotech industries. However, to make most of the data available and to solve industrial problems, a basic understanding of statistical methods is required. In this complimentary web seminar, Mia Stephens, Principal product manager at JMP, will present a case study showing how a company was able to solve a costly manufacturing problem and improved yield by applying statistical methods. She will introduce the free online training “Statistical Thinking for Industrial Problem Solving” that helps scientists and engineers to build practical skills in using data to solve problems better.

Speaker: Mia Stephens, Principal Product Manager, SAS Institute GmbH https://www.jmp.com 

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Free online course: Statistical thinking for industrial problem solving

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Using a data driven approach to deliver solutions

In virtually every field – across engineering, industry, science, academia and beyond – gaining insight from data is central to problem solving, innovation and growth. This is especially true when using chemistry to improve our health, our environment and our daily lives.

Software puts the statistical techniques that can be used to make sense of data within easy reach. But without understanding which approaches are useful, and how to check, interpret and communicate results, solutions may prove unworkable, and the best opportunities will remain undiscovered.

That’s why we created Statistical Thinking for Industrial Problem Solving.

Build your data skills online

Developed with industrial practitioners and academics worldwide, this online course is available – free of charge – to anyone interested in using data to solve problems.

The course aims to limit theoretical baggage using simulations, visualisations and practical examples to convey the key ideas required to make use of data with confidence. And rather than present the required statistical techniques in isolation, we use real-world industrial scenarios throughout the course.

This allows us to contextualise the use of statistical methods and illustrate how to link them together in a coordinated way to solve common industrial problems. If your company is focused on improvement rather than problem solving don’t worry, the ideas and techniques are relevant to both activities.

The course content was devised by experts from industry, academia and those with a foot in both camps. It includes seven modules of self-paced learning, totalling 25 to 30 hours.

In each three to five-hour long module you will learn how to define a problem and map a process, how to identify the data you need to solve your problem, how to explore this data and how to use it to make decisions. You also learn about quality methods and the tools for building statistical and predictive models.

Tracking a product journey: From bench to assembly line

Finally, we introduce statistically designed experiments to efficiently support the cycles of learning that take you from the bench to the manufacture of viable products.You can start at the beginning and work through the whole course, or just take selected modules.

Each module includes brief instructional and demonstration videos. There are also questions and exercises to test your understanding and allow you to practice what you have learned. A self-assessment quiz at the end of each module tracks how your knowledge is building. Achieving a pass grade at an end of module quiz gives you a badge that certifies successful completion of the content.

The software used throughout the course is JMP Pro, however, because the focus is the practical application of proven and powerful statistical techniques, the knowledge and skills you gain are transferrable. Familiarity with JMP software isn’t necessary and you will be given access to it in the virtual learning environment (VLE) when you register.

Because it’s in the cloud, you can access the course from any device, from anywhere, using the same login credentials. The course will be localised into other languages, so you don’t have to be an English speaker. Built from the ground up for the modern learner, the course is available 24-7, so you can work when and how you want.

Access the JMP User Community

Once enrolled in the course, you can ask questions or start a discussion on the JMP User Community. You also have free online access to the book JMP Start Statistics.

After completing all the course modules, you will have the option to obtain a formal certification in Statistical Thinking for Industrial Problem Solving. This performance-based certification can be used to demonstrate your mastery of this area to your institution, employer or potential employer.

We created Statistical Thinking for Industrial Problem Solving to meet the needs of industrially-oriented engineers, scientists and students who want to learn how to extract valuable information from data. It’s hard to find other internet-based resources with a similar scope, depth and focus. But it’s only useful to the extent that you engage with the content, try to master it and apply it to what you do. Why not give it a go?

Go to www.jmp.com/statisticalthinking and click Enroll Now. Accept the terms, and you’re on your way.

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• JMP Statistical Thinking for Industrial Problem Solving

JMP Statistical Thinking for Industrial Problem Solving equips the candidates with fundamentals of statistics and data. It comprises several modules that aim to teach the candidates about the comprehension, representation, interpretation, and communication of results derived from the available statistics. The JMP Statistical Thinking for Industrial Problem-Solving Certification will validate the skills and knowledge of the candidates in the above-mentioned domains.  For this, you will have to give a performance-based examination. The exam will test you with industrial problems based on statistical thinking and fundamental statistical methods.

Statistics and data are an integral aspect of almost every industry. And the analysis of the statistics is one of the essential steps to comprehend, process, and solve problems faced in various domains of an organization. With a proper understanding of data and stats, a professional has a correct approach to interpret and communicate results. Thus, it is important to back yourself with statistical thinking to add value to the organization you’re a part of.

Who should take this Exam?

Since the stats are an inseparable part of all the industries, this course can be taken by people from almost every work field. Candidates who are willing to add statistical thinking as a skill in their profile should go for this course.

Exam Details

How to Register?

Follow these steps to register for the exam –

• Firstly, visit the official site of SAS .
• Then, go on the credential tab and select JMP Statistical Thinking for Industrial Problem Solving.
• Further, scroll down to the “Take the Exam” section and click on Register for Exam .
• Then, you will be redirected to the website of Pearson VUE.
• Subsequently, Signup/Login to the Pearson VUE account.
• Then, Search for the IBM Big Data Engineer Exam.
• And finally, Select the Date, time, and confirm with the payment method.

Retake Policy

In case you fail the exam, you can reapply for the exam, but you will have to pay the exam fee again.

JMP Statistical Thinking for Industrial Problem Solving FAQ

For More Details See –  A00-910 FAQ | JMP Statistical Thinking for Industrial Problem Solving

Course Outline

The JMP Statistical Thinking for Industrial Problem Solving exam covers the following topics –

Statistical Thinking and Problem Solving: 10%

• First of all, defining statistical thinking and problem-solving.
• Secondly, defining the process for the creation of a process map or SIPOC.
• Thirdly, identifying the root causes of a problem, compile and collect data.

Exploratory Data Analysis: 20%

• Firstly, describing data using descriptive statistics and graphical summaries.
• Subsequently, visualizing and exploring data.
• Also, saving and sharing results.
• Moreover, preparing data for analysis.

Quality Methods: 20%

• First thing first, using Statistical Process Control Charts.
• Secondly, assessing process capability.
• Subsequently, conducting Measurement System Studies.

Decision Making with Data: 15%

• Firstly, defining/describing Statistical Intervals.
• Secondly, performing statistical tests.
• Thirdly, determining sample size.

Correlation and Regression: 20%

• To benign with, defining, and using correlation.
• Subsequently, defining simple linear regression.
• Consequently, defining/explaining multiple linear regression.
• Lastly, defining/explaining logistic regression.

Design of Experiments: 10%

• Firstly, defining DOE and compare it to OFAT.
• Secondly, discussing best practices and considerations to take when running an experiment.
• Thirdly, analyzing the results of an experiment.
• Last but not least, designing a simple experiment.

Predictive Modeling and Text Mining: 5%

• On one hand, explaining the difference between explanatory modeling versus predictive modeling.
• And, on the other hand, interpreting results from a predictive model with validation.

Preparatory Guide for JMP Statistical Thinking for Industrial Problem Solving (A00-910)

The JMP Statistical Thinking exam is a hard nut to crack. However, with the right strategy, you can get yourself certified for the skills and abilities in this domain. For this, it is essential to follow a guide so that you can keep your plans concentrated on scoring the best marks in the exam. To give you a bit of clarity, we have broken down the process to prepare for this exam in simpler components in a preparatory guide. This will be beneficial for you to figure out the right plan for your preparation. By implementing the steps in this preparatory guide, you will be able to increase your accuracy and efficiency.

Step 1 – Revise the Exam Objectives

To start with your preparations, the first thing you need to do is revise the exam objectives. This is because the structure and nature of the questions in the exam will be mainly dependent on these objectives. Also, before you start preparing for the exam, you must know what are the areas that candidates are expected to know about to clear the exam. Thus, being aware of these objectives is your initiating point.

The following are the objectives of the JMP Statistical Thinking for Industrial Problem-Solving exam –

• Firstly, explain the importance of using data and applying statistical methods to solve problems.
• Secondly, develop a clearly defined problem statement to translate a business problem into an analytics problem
• Thirdly, compile, and prepare data for analysis.
• Further, visually and interactively explore data to identify potential root causes of variation.
• Also, translate analytics results into actionable decisions and results.
• Further, interpret the components of a control chart to determine if a process is stable.
• Furthermore, design a measurement system analysis (MSA) and interpret the results of an MSA.
• Additionally, conduct a capability analysis and interpret Cp, Cpk, Pp, and Ppk.
• And lastly, interpret statistical intervals and hypothesis test results.
• Describe the impact of sampling and sample size on statistical decision making.
• Explain the difference between correlation and causation.
• Fit a simple regression model and interpret the results.
• Interpret analysis results for multiple linear regression and binary logistic regression.
• Explain the importance of DOE in developing knowledge of cause and effect.

Step 2 – Study Resources

The biggest factor in your preparations will be the resources you use to study. Statistical thinking is a topic that can have several resources offering knowledge and information in this field. However, to secure good scores, it is important to keep your efforts solely heading towards the topics covered under the exam. For this, it is always advised to rely only on authentic sources. The official website the most authentic source to know about the study material.  

Here, we are listing the training and books recommended by the official sources.

• Statistical Thinking for Industrial Problem Solving – A free online course by JMP
• White Polymer Case Study
• JMP Course Material Library
• JMP Start Statistics: A Guide to Statistics and Data Analysis Using JMP, Sixth Edition
• Practical Data Analysis with JMP
• Visual Six Sigma: Making Data Analysis
• Statistics with JMP: Hypothesis Tests, ANOVA and Regression

Step 3 – Join the JMP Community

Your preparations will be largely covered by the study material mentioned above. However, you can supplement your preparations by joining the JMP community. Here you can raise your queries and people who are more experienced will help you out with the solutions. Also, you can see what others have asked and also the answers to their questions. You can also help others with your knowledge and skills. The JMP community is a platform where people can connect, share, and communicate with professionals from all levels of expertise and experience.

Step 4 – Evaluate yourself with Practice Tests

After you have prepared for the exam, it is important to check your skills before facing the real exam. For this, practice tests can be helpful. The practice tests are a compilation of questions similar to the questions of the exam. These tests give you an experience of what the real exam is all about. With these practice tests, you can test yourself, and also learn how to manage the time during the exam. These practice tests will help you notice your shortcomings and highlight your strong points. The more tests you give, the better will be your confidence to face the actual exam. So, try a free test at testpreptraining.com.

Prepare for Assured Success

• Data Analysis courses

Statistical Thinking for Industrial Problem Solving, presented by JMP

Updated on Jan 1, 2022

Course overview

How to describe data with statistical summaries, and how to explore your data using advanced visualizations.

Understand statistical intervals, hypothesis tests and how to calculate sample size.

How to fit, evaluate and interpret linear and logistic regression models.

How to build predictive models and conduct a statistically designed experiment.

Description

Similar courses.

• Flexible deadline
• Certificate

English language

Recommended provider

Certificate available

Statistical Thinking for Industrial Problem Solving (STIPS)

A free online statistics course.

In virtually every field, deriving insights from data is central to problem solving, innovation and growth. But without an understanding of which approaches to use, and how to interpret and communicate results, the best opportunities will remain undiscovered.

That’s why we created Statistical Thinking for Industrial Problem Solving (STIPS). This online statistics course is available – for free – to anyone interested in building practical skills in using data to solve problems better.

Have two minutes? Learn more.

All you need is a browser, an internet connection and an inquisitive mind..

This course is comprised of seven modules, totaling about 30 hours of self-paced learning.  You can take one module or take them all. Each module includes short instructional videos, JMP demonstrations, questions and exercises. Review the full course outline page or PDF , or learn more about each module below:

Statistical Thinking and Problem Solving

Statistical thinking is about understanding, controlling and reducing process variation. Learn about process maps, problem-solving tools for defining and scoping your project, and understanding the data you need to solve your problem.

Exploratory Data Analysis

Learn the basics of how to describe data with graphics and statistical summaries. Then, learn how to use interactive visualizations to communicate the story in your data. You'll also learn some core steps in preparing your data for analysis.

Quality Methods

Learn about tools for quantifying, controlling and reducing variation in your product, service or process. Topics include control charts, process capability and measurement systems analysis.

Decision Making With Data

Learn about tools used for drawing inferences from data. In this module you learn about statistical intervals and hypothesis tests. You also learn how to calculate sample size and see the relationship between sample size and power.

Correlation and Regression

Learn how to use scatterplots and correlation to study the linear association between pairs of variables. Then, learn how to fit, evaluate and interpret linear and logistic regression models.

Design of Experiments

In this introduction to statistically designed experiments (DOE), you learn the language of DOE, and see how to design, conduct and analyze an experiment in JMP.

Predictive Modeling and Text Mining

Learn how to identify possible relationships, build predictive models and derive value from free-form text.

Teach with STIPS

Integrate STIPS content into your academic curriculum or commercial internal training using our customizable teaching materials.

• Request access to teaching materials

STIPS is excellent in balancing statistical theory and the practical hands-on use of JMP to solve common problems that many organizations deal with on a routine basis. Learn More

Pete Cannon , NVIDIA

I’m getting feedback from my students that they really like STIPS. It’s multimedia, it’s lively, things are well explained and they can complete it at their own pace. Just last week, one student told me ‘I think I finally understand statistics.’ Learn More

Phil Ramsey , University of New Hampshire

STIPS is a very good course. I was happy to have one online course concentrating a lot of important information in an easy, understandable level. Learn More

Andreas Trautmann , Lonza

The instructional method is excellent...The lessons are short and tight. They have just the right amount of complex information broken down into manageable chunks.

Award of Excellence , Society of Technical Communication

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You are here, statistical thinking for industrial problem solving.

This course is for anyone seeking to develop core competency in applied problem-solving with data and statistics. It addresses the Statistical Thinking for Industrial Problem Solving certification exam content areas and tasks.

This 25- to 30-hour e-learning course blends mini-lectures, case studies, demos, practices, and quizzes to provide an applied and interactive learning experience. Topics are grouped into seven stand-alone modules, and each module takes three to five hours to complete. Access to JMP software is provided in a virtual lab, along with the JMP Start Statistics eBook and other resources.

This course can help prepare you for the following certification exam(s):  JMP Certified Associate: Statistical Thinking for Industrial Problem Solving .

Learn how to

• Map a process, define and scope your project, and determine the data that you need to solve your problem.
• Describe data with graphics and use interactive visualizations to find and communicate the story in your data.
• Use tools to quantify, control, and reduce variation in your product, service, or process.
• Draw inferences from data, construct statistical intervals, perform hypothesis tests, and understand the relationship between sample size and power.
• Examine the linear association between pairs of variables.
• Fit and interpret linear and logistic regression models.
• Speak the language of design of experiments (DOE).
• Design, conduct, and analyze an experiment in JMP.
• Identify possible relationships, build predictive models, and derive value from free-form text.

SAS Institute

SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.

SAS is a business user software and is used in the entire industry, be it IT, Retail, Pharma, Banking and Finance, Retail, Manufacturing, etc. Besides it’s user-friendly software and easy to pick-up, the only pre-requisite is knowledge of MS-Office. Only for the Analytics course, one needs to know basic statistics. You could be from any back ground; no prior IT experience is required.

https://video.sas.com/category/videos/how-to-tutorials

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