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:
• Explain the importance of statistical thinking in solving problems
• Describe the importance of data, and the steps needed to compile and prepare data for analysis
• Compare core methods for summarizing, exploring and analyzing data, and describe when to apply these methods
• Recognize the importance of statistically designed experiments in understanding cause and effect
In this module you learn about the course and about accessing JMP software in this course.
What's included
3 videos4 readings1 app item
Show info about module content
3 videos•Total 13 minutes
Course Overview•2 minutes
Why You Need a Foundation in Statistical Thinking•4 minutes
First Time Using JMP? View the JMP Quickstart Video•7 minutes
4 readings•Total 5 minutes
Learner Prerequisites•1 minute
Taking this Course•2 minutes
Using Forums and Getting Help•1 minute
Using the JMP Virtual Lab•1 minute
1 app item•Total 60 minutes
Access the JMP Virtual Lab - New•60 minutes
Module 1: Statistical Thinking and Problem Solving
Module 2•2 hours to complete
Module details
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.
Activity: Developing a Cause-and-Effect Diagram•10 minutes
Read About It•5 minutes
Summary: Statistical Thinking and Problem Solving •1 minute
16 assignments•Total 19 minutes
Question 1.01•1 minute
Question 1.03•1 minute
Question 1.04•1 minute
Question 1.06•1 minute
Question 1.07•1 minute
Question 1.08•1 minute
Question 1.09•1 minute
Question 1.10•1 minute
Question 1.12•1 minute
Question 1.13•1 minute
Question 1.15•1 minute
Question 1.16•1 minute
Questions 1.18 - 1.19•2 minutes
Question 1.20•1 minute
Question 1.21•1 minute
Questions 1.23-1.25•3 minutes
1 app item•Total 20 minutes
Statistical Thinking and Problem Solving Quiz•20 minutes
7 plugins•Total 17 minutes
Think About it 1.02•2 minutes
Think About it 1.05•1 minute
Think About it 1.11•1 minute
Practice: Developing a SIPOC or I/O Map•10 minutes
Think About it 1.14•1 minute
Think About it 1.17•1 minute
Think About it 1.22•1 minute
Module 2A: Exploratory Data Analysis, Part 1
Module 3•7 hours to complete
Module details
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.
What's included
50 videos31 assignments1 app item4 plugins
Show info about module content
50 videos•Total 184 minutes
Introduction•1 minute
Introduction to Descriptive Statistics•2 minutes
Types of Data•5 minutes
Histograms•4 minutes
Demo: Creating Histograms in JMP•4 minutes
Demo: Saving Your Work Using Scripts•2 minutes
The Chemical Manufacturing Case Study•1 minute
The White Polymer Case Study•1 minute
Measures of Central Tendency and Location•6 minutes
Demo: Summarizing Continuous Data with the Distribution Platform•4 minutes
Demo: Summarizing Continuous Data with Column Viewer and Tabulate•4 minutes
Measures of Spread: Range and Interquartile Range•5 minutes
Demo: Hiding and Excluding Data•3 minutes
Measures of Spread: Variance and Standard Deviation•4 minutes
Visualizing Continuous Data•8 minutes
Demo: Creating Tabular Summaries with Tabulate•2 minutes
Demo: Creating Scatterplots and Scatterplot Matrices•3 minutes
Demo: Creating Comparative Box Plots with Graph Builder•2 minutes
Demo: Creating Run Charts (Line Graphs) with Graph Builder•2 minutes
Describing Categorical Data•5 minutes
Creating Tabular Summaries for Categorical Data•3 minutes
Demo: Creating Bar Charts and Mosaic Plots•4 minutes
Review and Introduction to Probability Concepts•2 minutes
Samples and Populations•4 minutes
Understanding the Normal Distribution•4 minutes
Checking for Normality•7 minutes
Demo: Checking for Normality•2 minutes
Demo: Finding the Area Under a Curve•3 minutes
The Central Limit Theorem•5 minutes
Demo: Exploring the Central Limit Theorem•3 minutes
Introduction to Exploratory Data Analysis•4 minutes
Demo: Adding Markers, Colors, and Row Legends•4 minutes
Demo: Switching Columns in an Analysis•2 minutes
Pareto Plots•6 minutes
Demo: Creating Sorted Bar Charts and Pareto Plots•3 minutes
Packed Bar Charts and Data Filtering•4 minutes
Demo: Creating Packed Bar Charts•2 minutes
Demo: Using the Local Data Filter•3 minutes
Tree Maps and Mosaic Plots•5 minutes
Demo: Creating a Tree Map•2 minutes
Using Trellis Plots and Overlay Variables•6 minutes
Demo: Creating Trellis Plots and Using Overlay Variables•3 minutes
Bubble Plots and Heat Maps•3 minutes
Demo: Creating Bubble Plots•4 minutes
Demo: Creating Heat Maps•3 minutes
Visualizing Geographic and Spatial Data•7 minutes
Demo: Creating a Geographic Map Using Shape Files•3 minutes
Demo: Creating Maps Using Coordinates•4 minutes
Summary of Exploratory Data Analysis Tools•3 minutes
31 assignments•Total 182 minutes
Question 2.01•2 minutes
Question 2.02•2 minutes
Practice: Understanding Yield for a Chemical Manufacturing Process•10 minutes
Practice: Exploring the Relationship Between Variables•10 minutes
Question 2.03 - 2.04•1 minute
Practice: Summarizing Continuous Data with the Distribution Platform•10 minutes
Question 2.06 - 2.07•2 minutes
Practice: Understanding Box Plots•10 minutes
Question 2.08•2 minutes
Question 2.09•2 minutes
Practice: Visualizing Continuous Data•10 minutes
Question 2.10 - 2.11•2 minutes
Practice: Visualizing Categorical Data•10 minutes
Question 2.13•1 minute
Question 2.15•1 minute
Practice: Checking for Normality•10 minutes
Practice: Recognizing Shapes in Normal Quantile Plots•10 minutes
Practice: Exploring the Central Limit Theorem•10 minutes
Question 2.16•1 minute
Practice: Exploring Many Variables Using the Column Switcher•10 minutes
Question 2.17 - 2.18•2 minutes
Practice: Creating Sorted Bar Charts in JMP•10 minutes
Question 2.19•1 minute
Practice: Exploring Data with a Local Data Filter•10 minutes
Question 2.20•1 minute
Practice: Exploring Data with a Tree Map and Mosaic Plot•10 minutes
Practice: Exploring Data Using Trellis Plots•10 minutes
Question 2.21•1 minute
Practice: Exploring Data Using Bubble Plots and Heat Maps•10 minutes
Question 2.22•1 minute
Practice: Exploring Data with a Geographic Map•10 minutes
1 app item•Total 60 minutes
Access the JMP Virtual Lab - New•60 minutes
4 plugins•Total 11 minutes
Think About It 2.05•2 minutes
Think About It 2.12•2 minutes
Think About It 2.14•2 minutes
Try It and Think About It 2.12•5 minutes
Module 2B: Exploratory Data Analysis, Part 2
Module 4•7 hours to complete
Module details
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.
Evaluating the Effectiveness of a Visualization•5 minutes
Designing an Effective Visualization: Part 1•4 minutes
Designing an Effective Visualization: Part 2•6 minutes
Communicating Visually with Animation•3 minutes
Designing for Your Audience•4 minutes
Understanding Your Target Audience•5 minutes
Designing Visualizations for Communication•1 minute
Designing Visualizations: The Do's•5 minutes
Designing Visualizations: The Don'ts•2 minutes
Demo: Customizing Graphics•4 minutes
Introduction to Saving and Sharing Results•2 minutes
Saving and Sharing Results in JMP•3 minutes
Saving and Sharing Results outside of JMP•3 minutes
Deciding Which Format to Use•1 minute
Demo: Organizing Your Saved Scripts•3 minutes
Demo: Combining JMP Scripts for Analyses•3 minutes
Demo: Sharing Static Output•3 minutes
Demo: Saving Your Work in a JMP Journal•4 minutes
Data Tables Essentials•2 minutes
Common Data Quality Issues•5 minutes
Identifying Issues in the Data Table•4 minutes
Identifying Issues One Variable at a Time•4 minutes
Summarizing What You Have Learned•4 minutes
Demo: Exploring Missing Values•3 minutes
Demo: Using Recode•3 minutes
Restructuring Data for Analysis•3 minutes
Demo: Stacking and Splitting Data•2 minutes
Combining Data•3 minutes
Demo: Concatenating Data Tables•2 minutes
Demo: Joining Data Tables•3 minutes
Deriving New Variables•2 minutes
Demo: Binning Data Using Conditional IF-THEN Statements•3 minutes
Demo: Transforming Data•3 minutes
Working with Dates•2 minutes
2 readings•Total 3 minutes
Read About It•2 minutes
Summary - Exploratory Data Analysis•1 minute
31 assignments•Total 204 minutes
Question 2.24•1 minute
Question 2.25•1 minute
Question 2.26•2 minutes
Question 2.28 - 2.29•2 minutes
Practice: Customizing Graphics•10 minutes
Practice: Creating a Slope Graph•10 minutes
Question 2.31 - 2.32•2 minutes
Question 2.33•1 minute
Practice: Exploring Reports Published on JMP Public•10 minutes
Practice: Grouping and Combining Analysis Scripts•10 minutes
Practice: Creating a Simple Dashboard•10 minutes
Practice: Using a JMP Journal to Document Your Work•10 minutes
Question 2.34•2 minutes
Question 2.35•2 minutes
Practice: Creating the Formula for Scrap Rate•10 minutes
Practice: Checking the Data Table for Issues•10 minutes
Question 2.36•1 minute
Practice: Checking Data Quality with Summary Statistics and Graphs•10 minutes
Question 2.37 - 2.38•2 minutes
Question 2.39•1 minute
Practice: Exploring Missing Data•15 minutes
Practice: Recoding Missing Values•10 minutes
Practice: Using Recode to Bin Data•10 minutes
Question 2.40•1 minute
Practice: Stacking Data•10 minutes
Question 2.41•1 minute
Practice: Concatenating Data Tables•10 minutes
Practice: Joining Data Tables•10 minutes
Practice: Creating a Binning Formula•10 minutes
Practice: Extracting Information from a Column•10 minutes
Practice: Working with Dates•10 minutes
2 app items•Total 80 minutes
Access the JMP Virtual Lab - New•60 minutes
Exploratory Data Analysis Quiz•20 minutes
2 plugins•Total 7 minutes
Think About It and Try It 2.27•5 minutes
Think About It 2.30•2 minutes
Module 3: Quality Methods
Module 5•7 hours to complete
Module details
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.
Practice: Conducting a Capability Analysis with a Phase Variable•10 minutes
Practice: Conducting a Capability Analysis with Nonnormal Data•10 minutes
Question 3.12•2 minutes
Question 3.13•1 minute
Practice: Designing a Gauge Study•10 minutes
Practice: Visualizing the Area Measurement MSA Data•10 minutes
Practice: Visualizing the MFI MSA Data•10 minutes
Practice: Analyze the Area Measurement MSA Data•10 minutes
Practice: Analyzing the Melt Flow Index MSA•10 minutes
Question 3.15•1 minute
2 app items•Total 80 minutes
Access the JMP Virtual Lab - New•60 minutes
Quality Methods Quiz•20 minutes
2 plugins•Total 3 minutes
Think About It 3.01•2 minutes
Think About It 3.14•1 minute
Module 4: Decision Making with Data
Module 6•7 hours to complete
Module details
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.
Introduction to Decision Making with Data•1 minute
Introduction to Statistical Inference•3 minutes
What Is a Confidence Interval?•2 minutes
A Practical Example•2 minutes
Estimating a Mean•5 minutes
Visualizing Sampling Variation•4 minutes
Constructing Confidence Intervals•5 minutes
Demo: Understanding the Confidence Level and Alpha Risk•3 minutes
Demo: Calculating Confidence Intervals•2 minutes
Prediction Intervals•4 minutes
Tolerance Intervals•5 minutes
Demo: Calculating Prediction and Tolerance Intervals•3 minutes
Comparing Interval Estimates•2 minutes
Introduction to Statistical Testing•1 minute
Statistical Decision Making•5 minutes
Understanding the Null and Alternative Hypothesis•3 minutes
Sampling Distribution under the Null•4 minutes
The p-Value and Statistical Significance•5 minutes
Summary of Foundations in Statistical Testing•2 minutes
Conducting a One-Sample t Test•6 minutes
Demo: Conducting a One-Sample t Test•4 minutes
Demo: Understanding p-Values and t Ratios•3 minutes
Equivalence Testing•3 minutes
Comparing Two Means•4 minutes
Two-Sample t Tests•5 minutes
Unequal Variances Tests•2 minutes
Demo: Conducting a Two-Sample t Test•4 minutes
Paired Observations•5 minutes
Demo: Performing a Paired t Test•2 minutes
Comparing More Than Two Means•3 minutes
One-Way ANOVA (Analysis of Variance)•6 minutes
Multiple Comparisons•4 minutes
Demo: Comparing More Than Two Means•5 minutes
Revisiting Statistical Versus Practical Significance•3 minutes
Summary of Hypothesis Testing for Continuous Data•2 minutes
Introduction to Sample Size and Power•3 minutes
Sample Size for a Confidence Interval for the Mean•4 minutes
Demo: Calculating the Sample Size for a Confidence Interval•3 minutes
Outcomes of Statistical Tests•6 minutes
Statistical Power•3 minutes
Exploring Sample Size and Power•5 minutes
Demo: Exploring the Power Animation•3 minutes
Calculating the Sample Size for One-Sample t Tests•2 minutes
Demo: Calculating the Sample Size for a One-Sample t Test•2 minutes
Calculating the Sample Size for Two-Sample t Tests•2 minutes
Demo: Calculating the Sample Size for Two or More Sample Means•3 minutes
Summary of Sample Size and Power•2 minutes
2 readings•Total 2 minutes
Read About It•1 minute
Summary: Decision Making with Data•1 minute
38 assignments•Total 207 minutes
Question 4.01•1 minute
Question 4.02•1 minute
Question 4.03•1 minute
Questions 4.04 - 4.06•2 minutes
Practice: Constructing a Confidence Interval•10 minutes
Practice: Comparing Intervals at Different Confidence Levels•10 minutes
Practice: Constructing a Confidence Interval for the Speed of Light•10 minutes
Question 4.07•1 minute
Question 4.08•1 minute
Practice: Constructing Prediction and Tolerance Intervals•10 minutes
Question 4.09•2 minutes
Practice: Comparing Interval Estimates•10 minutes
Question 4.11•1 minute
Questions 4.12 - 4.14•3 minutes
Question 4.15•1 minute
Questions 4.16 - 4.18•3 minutes
Question 4.20•1 minute
Practice: Conducting a One-Sample t Test•10 minutes
Practice: Conducting a One-Sample t Test with a BY Variable•10 minutes
Practice: Conducting an Equivalence Test•10 minutes
Question 4.21•1 minute
Practice: Conducting a Two-Sample t Test•10 minutes
Practice: Conducting an Equivalence Test for Two Means•10 minutes
Practice: Conducting an Unequal Variances Test•10 minutes
Question 4.22•1 minute
Practice: Conducting a Paired t Test•10 minutes
Question 4.23•1 minute
Practice: Conducting a One-Way ANOVA Analysis•10 minutes
Practice: Comparing Several Means•10 minutes
Question 4.25•1 minute
Question 4.26•1 minute
Practice: Calculating Sample Size for a CI for a Mean•10 minutes
Practice: Calculating Sample Size for a CI for a Proportion•10 minutes
Question 4.27 - 4.28•2 minutes
Question 4.30•1 minute
Question 4.31•1 minute
Practice: Calculating Sample Size for a One-Sample t Test•10 minutes
Practice: Calculating Sample Size for a Two-Sample t Test•10 minutes
2 app items•Total 80 minutes
Access the JMP Virtual Lab - New•60 minutes
Decision Making with Data Quiz•20 minutes
5 plugins•Total 5 minutes
Think About it 4.10•1 minute
Think About it 4.19•1 minute
Think About it 4.24•1 minute
Question 4.29•1 minute
Think About it 4.32•1 minute
Module 5: Correlation and Regression
Module 7•7 hours to complete
Module details
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.
Practice: Identifying Outliers and Influential Observations•10 minutes
Question 5.11•1 minute
Practice: Fitting a Model with Categorical Predictors•10 minutes
Question 5.12•1 minute
Practice: Fitting a Model with Interactions•10 minutes
Practice: Selecting Variables Using Effect Summary•10 minutes
Question 5.14•1 minute
Question 5.15•1 minute
Practice: Regression Modeling Mini Case Study•10 minutes
Question 5.16•1 minute
Question 5.17•2 minutes
Practice: Fitting a Simple Logistic Model for Reaction Time•10 minutes
Practice: Fitting a Multiple Logistic Regression Model•10 minutes
Practice: Fitting a Logistic Regression Model with Interactions•10 minutes
2 app items•Total 80 minutes
Access the JMP Virtual Lab - New•60 minutes
Correlation and Regression Quiz•20 minutes
5 plugins•Total 5 minutes
Think About It 5.04•1 minute
Think About It 5.07•1 minute
Think About It 5.13•1 minute
Think About It 5.18•1 minute
Think About it 5.19•1 minute
Module 6: Design of Experiments (DOE)
Module 8•6 hours to complete
Module details
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.
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What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.