Statistical Thinking for Industrial Problem Solving is an applied statistics course for scientists and engineers offered by JMP, a division of SAS. By completing this course, students will understand the importance of statistical thinking, and will be able to use data and basic statistical methods to solve many real-world problems. Students completing this course will be able to:

Offered By

## Statistical Thinking for Industrial Problem Solving, presented by JMP

SAS## About this Course

No prior knowledge of statistics or experience with JMP software is required.

## What you will learn

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.

## Skills you will gain

- Experimental Design
- Data Analysis
- Data Visualization (DataViz)
- Statistical Hypothesis Testing
- Statistics

No prior knowledge of statistics or experience with JMP software is required.

## Offered by

### SAS

Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. 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 SASÂ®, you can discover insights from your data and make sense of it all. Identify whatâ€™s working and fix what isnâ€™t. Make more intelligent decisions. And drive relevant change.

## Syllabus - What you will learn from this course

**19 minutes to complete**

## Course Overview

In this module you learn about the course and about accessing JMP software in this course.

**19 minutes to complete**

**2 hours to complete**

## 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.

**2 hours to complete**

**6 hours to complete**

## 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. Youâ€™ll also learn some core concepts in probability, which form the foundation of many methods you learn throughout this course.

**6 hours to complete**

**6 hours to complete**

## 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.

**6 hours to complete**

**6 hours to complete**

## 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.

**6 hours to complete**

## Reviews

- 5 stars87.30%
- 4 stars11.11%
- 1 star1.58%

### TOP REVIEWS FROM STATISTICAL THINKING FOR INDUSTRIAL PROBLEM SOLVING, PRESENTED BY JMP

Really good course, learnt a tremendous amount.

Thanks

one of the best course for data discovery , nice example and flow of course

It is a really exhilarating course testing your practical and theoretical understanding about the subject covering most fields in the topic of data analytics along with jmp, a user-friendly platform.

Awesome course. The course is really big, but awesome. It teaches a lot of things about problem solving, statistics, visualization, and of course how to use the software.

## Frequently Asked Questions

When will I have access to the lectures and assignments?

What will I get if I purchase the Certificate?

Is financial aid available?

More questions? Visit the Learner Help Center.