Mia Stephens 另外 +1 位授課教師

提供方

Statistical Thinking for Industrial Problem Solving, presented by JMP

SAS

課程信息

34,385 次近期查看

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

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初級

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

完成時間大約為44 小時

英語（English）

字幕：法語（French）, （歐洲人講的）葡萄牙語, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）

您將學到的內容有

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.

您將獲得的技能

Experimental DesignData AnalysisData Visualization (DataViz)Statistical Hypothesis TestingStatistics

可分享的證書

完成後獲得證書

100% 在線

立即開始，按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

初級

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

完成時間大約為44 小時

英語（English）

字幕：法語（French）, （歐洲人講的）葡萄牙語, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）

講師

授課教師評分

4.69/5 （14 個評分）

Mia Stephens

JMP Principal Product Manager

2,182 個學生

1 門課程

Ledi Trutna

Analytical Training Consultant

SAS Education

2,182 個學生

1 門課程

提供方

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 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.

教學大綱 - 您將從這門課程中學到什麼

週

週 1

完成時間為 19 分鐘

Course Overview

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

完成時間為 19 分鐘

3 個視頻（總計 13 分鐘）, 4 個閱讀材料, 1 個測驗

3 個視頻

Course Overview2分鐘

Why You Need a Foundation in Statistical Thinking4分鐘

First Time Using JMP? View the JMP Quickstart Video6分鐘

4 個閱讀材料

Learner Prerequisites1分鐘

Taking this Course2分鐘

Using Forums and Getting Help1分鐘

Using the JMP Virtual Lab1分鐘

完成時間為 2 小時

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.

完成時間為 2 小時

26 個視頻（總計 72 分鐘）, 3 個閱讀材料, 17 個測驗

26 個視頻

Introduction36

What Is Statistical Thinking?4分鐘

Overview of Problem Solving2分鐘

Statistical Problem Solving1分鐘

Types of Problems2分鐘

Defining the Problem3分鐘

Goals and Key Performance Indicators3分鐘

The White Polymer Case Study2分鐘

What Is a Process?3分鐘

Developing a SIPOC Map1分鐘

Developing an Input/Output Process Map4分鐘

Top-Down and Deployment Flowcharts2分鐘

Summary2分鐘

Tools for Identifying Potential Causes2分鐘

Brainstorming4分鐘

Multi-voting2分鐘

Using Affinity Diagrams2分鐘

Cause-and-Effect Diagrams4分鐘

The 5 Whys1分鐘

Cause-and-Effect Matrices1分鐘

Summary1分鐘

Data Collection for Problem Solving2分鐘

Types of Data2分鐘

Operational Definitions4分鐘

Data Collection Strategies4分鐘

Importing Data for Analysis1分鐘

3 個閱讀材料

Activity: Developing a Cause-and-Effect Diagram10分鐘

Read About It5分鐘

Summary: Statistical Thinking and Problem Solving 1分鐘

16 個練習

Question 1.011分鐘

Question 1.031分鐘

Question 1.041分鐘

Question 1.061分鐘

Question 1.071分鐘

Question 1.081分鐘

Question 1.091分鐘

Question 1.101分鐘

Question 1.121分鐘

Question 1.131分鐘

Question 1.151分鐘

Question 1.161分鐘

Questions 1.18 - 1.192分鐘

Question 1.201分鐘

Question 1.211分鐘

Questions 1.23-1.253分鐘

週

週 2

完成時間為 6 小時

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.

完成時間為 6 小時

50 個視頻（總計 184 分鐘）

50 個視頻

Introduction47

Introduction to Descriptive Statistics1分鐘

Types of Data5分鐘

Histograms4分鐘

Demo: Creating Histograms in JMP4分鐘

Demo: Saving Your Work Using Scripts1分鐘

The Chemical Manufacturing Case Study38

The White Polymer Case Study1分鐘

Measures of Central Tendency and Location6分鐘

Demo: Summarizing Continuous Data with the Distribution Platform4分鐘

Demo: Summarizing Continuous Data with Column Viewer and Tabulate4分鐘

Measures of Spread: Range and Interquartile Range5分鐘

Demo: Hiding and Excluding Data2分鐘

Measures of Spread: Variance and Standard Deviation4分鐘

Visualizing Continuous Data7分鐘

Demo: Creating Tabular Summaries with Tabulate2分鐘

Demo: Creating Scatterplots and Scatterplot Matrices3分鐘

Demo: Creating Comparative Box Plots with Graph Builder2分鐘

Demo: Creating Run Charts (Line Graphs) with Graph Builder2分鐘

Describing Categorical Data5分鐘

Creating Tabular Summaries for Categorical Data3分鐘

Demo: Creating Bar Charts and Mosaic Plots4分鐘

Review and Introduction to Probability Concepts2分鐘

Samples and Populations4分鐘

Understanding the Normal Distribution3分鐘

Checking for Normality6分鐘

Demo: Checking for Normality2分鐘

Demo: Finding the Area Under a Curve2分鐘

The Central Limit Theorem4分鐘

Demo: Exploring the Central Limit Theorem3分鐘

Introduction to Exploratory Data Analysis3分鐘

Exploring Continuous Data: Enhanced Tools6分鐘

Demo: Adding Markers, Colors, and Row Legends3分鐘

Demo: Switching Columns in an Analysis2分鐘

Pareto Plots6分鐘

Demo: Creating Sorted Bar Charts and Pareto Plots3分鐘

Packed Bar Charts and Data Filtering3分鐘

Demo: Creating Packed Bar Charts2分鐘

Demo: Using the Local Data Filter3分鐘

Tree Maps and Mosaic Plots4分鐘

Demo: Creating a Tree Map2分鐘

Using Trellis Plots and Overlay Variables5分鐘

Demo: Creating Trellis Plots and Using Overlay Variables3分鐘

Bubble Plots and Heat Maps2分鐘

Demo: Creating Bubble Plots3分鐘

Demo: Creating Heat Maps3分鐘

Visualizing Geographic and Spatial Data6分鐘

Demo: Creating a Geographic Map Using Shape Files2分鐘

Demo: Creating Maps Using Coordinates3分鐘

Summary of Exploratory Data Analysis Tools2分鐘

31 個練習

Question 2.012分鐘

Question 2.022分鐘

Practice: Understanding Yield for a Chemical Manufacturing Process10分鐘

Practice: Exploring the Relationship Between Variables10分鐘

Question 2.03 - 2.041分鐘

Practice: Summarizing Continuous Data with the Distribution Platform10分鐘

Question 2.06 - 2.072分鐘

Practice: Understanding Box Plots10分鐘

Question 2.082分鐘

Question 2.092分鐘

Practice: Visualizing Continuous Data10分鐘

Question 2.10 - 2.112分鐘

Practice: Visualizing Categorical Data10分鐘

Question 2.131分鐘

Question 2.151分鐘

Practice: Checking for Normality10分鐘

Practice: Recognizing Shapes in Normal Quantile Plots10分鐘

Practice: Exploring the Central Limit Theorem10分鐘

Question 2.161分鐘

Practice: Exploring Many Variables Using the Column Switcher10分鐘

Question 2.17 - 2.182分鐘

Practice: Creating Sorted Bar Charts in JMP10分鐘

Question 2.191分鐘

Practice: Exploring Data with a Local Data Filter10分鐘

Question 2.201分鐘

Practice: Exploring Data with a Tree Map and Mosaic Plot10分鐘

Practice: Exploring Data Using Trellis Plots10分鐘

Question 2.211分鐘

Practice: Exploring Data Using Bubble Plots and Heat Maps10分鐘

Question 2.221分鐘

Practice: Exploring Data with a Geographic Map10分鐘

週

週 3

完成時間為 6 小時

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.

完成時間為 6 小時

36 個視頻（總計 114 分鐘）, 2 個閱讀材料, 33 個測驗

36 個視頻

Introduction to Communicating with Data3分鐘

Creating Effective Visualizations1分鐘

Evaluating the Effectiveness of a Visualization4分鐘

Designing an Effective Visualization: Part 13分鐘

Designing an Effective Visualization: Part 25分鐘

Communicating Visually with Animation2分鐘

Designing for Your Audience3分鐘

Understanding Your Target Audience5分鐘

Designing Visualizations for Communication52

Designing Visualizations: The Do's5分鐘

Designing Visualizations: The Don'ts2分鐘

Demo: Customizing Graphics3分鐘

Introduction to Saving and Sharing Results2分鐘

Saving and Sharing Results in JMP3分鐘

Saving and Sharing Results outside of JMP3分鐘

Deciding Which Format to Use1分鐘

Demo: Organizing Your Saved Scripts2分鐘

Demo: Combining JMP Scripts for Analyses3分鐘

Demo: Sharing Static Output2分鐘

Demo: Saving Your Work in a JMP Journal4分鐘

Data Tables Essentials2分鐘

Common Data Quality Issues5分鐘

Identifying Issues in the Data Table4分鐘

Identifying Issues One Variable at a Time3分鐘

Summarizing What You Have Learned3分鐘

Demo: Exploring Missing Values3分鐘

Demo: Using Recode3分鐘

Restructuring Data for Analysis2分鐘

Demo: Stacking and Splitting Data2分鐘

Combining Data2分鐘

Demo: Concatenating Data Tables1分鐘

Demo: Joining Data Tables2分鐘

Deriving New Variables2分鐘

Demo: Binning Data Using Conditional IF-THEN Statements3分鐘

Demo: Transforming Data2分鐘

Working with Dates1分鐘

2 個閱讀材料

Read About It2分鐘

Summary - Exploratory Data Analysis1分鐘

31 個練習

Question 2.241分鐘

Question 2.251分鐘

Question 2.262分鐘

Question 2.28 - 2.292分鐘

Practice: Customizing Graphics10分鐘

Practice: Creating a Slope Graph10分鐘

Question 2.31 - 2.322分鐘

Question 2.331分鐘

Practice: Exploring Reports Published on JMP Public10分鐘

Practice: Grouping and Combining Analysis Scripts10分鐘

Practice: Creating a Simple Dashboard10分鐘

Practice: Using a JMP Journal to Document Your Work10分鐘

Question 2.342分鐘

Question 2.352分鐘

Practice: Creating the Formula for Scrap Rate10分鐘

Practice: Checking the Data Table for Issues10分鐘

Question 2.361分鐘

Practice: Checking Data Quality with Summary Statistics and Graphs10分鐘

Question 2.37 - 2.382分鐘

Question 2.391分鐘

Practice: Exploring Missing Data15分鐘

Practice: Recoding Missing Values10分鐘

Practice: Using Recode to Bin Data10分鐘

Question 2.401分鐘

Practice: Stacking Data10分鐘

Question 2.411分鐘

Practice: Concatenating Data Tables10分鐘

Practice: Joining Data Tables10分鐘

Practice: Creating a Binning Formula10分鐘

Practice: Extracting Information from a Column10分鐘

Practice: Working with Dates10分鐘

週

週 4

完成時間為 6 小時

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.

完成時間為 6 小時

41 個視頻（總計 154 分鐘）, 3 個閱讀材料, 28 個測驗

41 個視頻

Introduction41

Quality Methods Overview4分鐘

Introduction to Control Charts6分鐘

Individual and Moving Range Charts4分鐘

Demo: Creating an I and MR Chart Using the Control Chart Builder2分鐘

Common Cause versus Special Cause Variation6分鐘

Testing for Special Causes6分鐘

Demo: Testing for Special Causes in the Control Chart Builder2分鐘

X-bar and R and X-bar and S Charts3分鐘

Demo: Creating X-bar and R and X-bar and S Charts2分鐘

Rational Subgrouping4分鐘

3-Way Control Charts2分鐘

Demo: Creating 3-Way Control Charts2分鐘

Control Charts with Phases3分鐘

Demo: Adding Phases to Control Charts1分鐘

The Voice of the Customer2分鐘

Process Capability Indices5分鐘

Short- and Long-Term Estimates of Capability2分鐘

Understanding Capability for Process Improvement4分鐘

Estimating Process Capability: An Example4分鐘

Demo: Calculating Capability Indices Using the Distribution Platform5分鐘

Demo: Conducting a Capability Analysis Using the Control Chart Builder2分鐘

Calculating Capability for Nonnormal Data3分鐘

Demo: Estimating Capability for Nonnormal Data3分鐘

Estimating Process Capability for Many Variables2分鐘

Identifying Poorly Performing Processes4分鐘

Demo: Identifying Poorly Performing Processes5分鐘

A View from Industry6分鐘

What is a Measurement Systems Analysis2分鐘

Language and Terminology4分鐘

Designing a Measurement System Study2分鐘

Designing and Conducting an MSA4分鐘

Demo: Creating a Gauge Study Worksheet1分鐘

Analyzing an MSA with Visualizations6分鐘

Demo: Visualizing Measurement System Variation4分鐘

Analyzing the MSA4分鐘

Demo: Analyzing an MSA2分鐘

Demo: Conducting a Gauge R&R Analysis4分鐘

Studying Measurement System Accuracy3分鐘

Demo: Analyzing Measurement System Bias2分鐘

Improving the Measurement Process2分鐘

3 個閱讀材料

Activity: Area MSA5分鐘

Read About It1分鐘

Summary: Quality Methods1分鐘

26 個練習

Question 3.021分鐘

Practice: Creating an I and MR Chart10分鐘

Question 3.032分鐘

Question 3.041分鐘

Practice: Creating I and MR Charts for the White Polymer Case Study10分鐘

Practice: Constructing an X-Bar and S Chart10分鐘

Question 3.051分鐘

Question 3.061分鐘

Practice: Evaluating whether Improvements Have Been Sustained10分鐘

Practice: Using Control Charts as an Exploratory Tool10分鐘

Question 3.071分鐘

Question 3.082分鐘

Activity: Calculating Capability Indices2分鐘

Question 3.091分鐘

Question 3.10 - 3.112分鐘

Practice: Calculating Capability Indices10分鐘

Practice: Conducting a Capability Analysis with a Phase Variable10分鐘

Practice: Conducting a Capability Analysis with Nonnormal Data10分鐘

Question 3.122分鐘

Question 3.131分鐘

Practice: Designing a Gauge Study10分鐘

Practice: Visualizing the Area Measurement MSA Data10分鐘

Practice: Visualizing the MFI MSA Data10分鐘

Practice: Analyze the Area Measurement MSA Data10分鐘

Practice: Analyzing the Melt Flow Index MSA10分鐘

Question 3.151分鐘

週

週 5

完成時間為 7 小時

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.

完成時間為 7 小時

47 個視頻（總計 156 分鐘）, 2 個閱讀材料, 40 個測驗

47 個視頻

Introduction to Decision Making with Data1分鐘

Introduction to Statistical Inference3分鐘

What Is a Confidence Interval?2分鐘

A Practical Example1分鐘

Estimating a Mean4分鐘

Visualizing Sampling Variation3分鐘

Constructing Confidence Intervals4分鐘

Demo: Understanding the Confidence Level and Alpha Risk2分鐘

Demo: Calculating Confidence Intervals1分鐘

Prediction Intervals3分鐘

Tolerance Intervals4分鐘

Demo: Calculating Prediction and Tolerance Intervals2分鐘

Comparing Interval Estimates1分鐘

Introduction to Statistical Testing1分鐘

Statistical Decision Making5分鐘

Understanding the Null and Alternative Hypothesis3分鐘

Sampling Distribution under the Null3分鐘

The p-Value and Statistical Significance4分鐘

Summary of Foundations in Statistical Testing1分鐘

Conducting a One-Sample t Test6分鐘

Demo: Conducting a One-Sample t Test3分鐘

Demo: Understanding p-Values and t Ratios3分鐘

Equivalence Testing3分鐘

Comparing Two Means3分鐘

Two-Sample t Tests4分鐘

Unequal Variances Tests1分鐘

Demo: Conducting a Two-Sample t Test3分鐘

Paired Observations5分鐘

Demo: Performing a Paired t Test1分鐘

Comparing More Than Two Means2分鐘

One-Way ANOVA (Analysis of Variance)5分鐘

Multiple Comparisons3分鐘

Demo: Comparing More Than Two Means4分鐘

Revisiting Statistical Versus Practical Significance2分鐘

Summary of Hypothesis Testing for Continuous Data1分鐘

Introduction to Sample Size and Power2分鐘

Sample Size for a Confidence Interval for the Mean4分鐘

Demo: Calculating the Sample Size for a Confidence Interval3分鐘

Outcomes of Statistical Tests5分鐘

Statistical Power2分鐘

Exploring Sample Size and Power4分鐘

Demo: Exploring the Power Animation2分鐘

Calculating the Sample Size for One-Sample t Tests2分鐘

Demo: Calculating the Sample Size for a One-Sample t Test2分鐘

Calculating the Sample Size for Two-Sample t Tests2分鐘

Demo: Calculating the Sample Size for Two or More Sample Means3分鐘

Summary of Sample Size and Power1分鐘

2 個閱讀材料

Read About It1分鐘

Summary: Decision Making with Data1分鐘

38 個練習

Question 4.011分鐘

Question 4.021分鐘

Question 4.031分鐘

Questions 4.04 - 4.062分鐘

Practice: Constructing a Confidence Interval10分鐘

Practice: Comparing Intervals at Different Confidence Levels10分鐘

Practice: Constructing a Confidence Interval for the Speed of Light10分鐘

Question 4.071分鐘

Question 4.081分鐘

Practice: Constructing Prediction and Tolerance Intervals10分鐘

Question 4.092分鐘

Practice: Comparing Interval Estimates10分鐘

Question 4.111分鐘

Questions 4.12 - 4.143分鐘

Question 4.151分鐘

Questions 4.16 - 4.183分鐘

Question 4.201分鐘

Practice: Conducting a One-Sample t Test10分鐘

Practice: Conducting a One-Sample t Test with a BY Variable10分鐘

Practice: Conducting an Equivalence Test10分鐘

Question 4.211分鐘

Practice: Conducting a Two-Sample t Test10分鐘

Practice: Conducting an Equivalence Test for Two Means10分鐘

Practice: Conducting an Unequal Variances Test10分鐘

Question 4.221分鐘

Practice: Conducting a Paired t Test10分鐘

Question 4.231分鐘

Practice: Conducting a One-Way ANOVA Analysis10分鐘

Practice: Comparing Several Means10分鐘

Question 4.251分鐘

Question 4.261分鐘

Practice: Calculating Sample Size for a CI for a Mean10分鐘

Practice: Calculating Sample Size for a CI for a Proportion10分鐘

Question 4.27 - 4.282分鐘

Question 4.301分鐘

Question 4.311分鐘

Practice: Calculating Sample Size for a One-Sample t Test10分鐘

Practice: Calculating Sample Size for a Two-Sample t Test10分鐘

週

週 6

完成時間為 6 小時

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.

完成時間為 6 小時

43 個視頻（總計 150 分鐘）, 2 個閱讀材料, 32 個測驗

43 個視頻

Introduction34

What Is Correlation?2分鐘

Interpreting Correlation2分鐘

Demo: Exploring the Impact of Outliers on Correlation1分鐘

Demo: Assessing Correlations3分鐘

Introduction to Regression Analysis6分鐘

Demo: Fitting a Regression Model2分鐘

The Simple Linear Regression Model4分鐘

The Method of Least Squares1分鐘

Demo: The Method of Least Squares1分鐘

Visualizing the Method of Least Squares1分鐘

Regression Model Assumptions5分鐘

Demo: Evaluating Model Assumptions1分鐘

Interpreting Regression Results6分鐘

Demo: Interpreting Regression Analysis Results3分鐘

Fitting a Model with Curvature3分鐘

Demo: Fitting Polynomial Models2分鐘

What is Multiple Linear Regression?3分鐘

Fitting the Multiple Linear Regression Model5分鐘

Demo: Fitting Multiple Linear Regression Models2分鐘

Interpreting Results in Explanatory Modeling6分鐘

Demo: Using the Prediction Profiler2分鐘

Residual Analysis and Outliers6分鐘

Demo: Analyzing Residuals and Outliers2分鐘

Multiple Linear Regression with Categorical Predictors5分鐘

Demo: Fitting a Model with Categorical Predictors1分鐘

Multiple Linear Regression with Interactions5分鐘

Demo: Fitting a Model with Interactions2分鐘

Variable Selection6分鐘

Demo: Selecting Variables Using Effect Summary2分鐘

Multicollinearity4分鐘

Demo: Assessing Multicollinearity2分鐘

Closing Thoughts on Multiple Linear Regression2分鐘

What Is Logistic Regression?2分鐘

The Simple Logistic Model4分鐘

Simple Logistic Regression Example3分鐘

Interpreting Logistic Regression Results3分鐘

Demo: Fitting a Simple Logistic Regression Model4分鐘

Multiple Logistic Regression4分鐘

Demo: Fitting a Multiple Logistic Regression Model2分鐘

Logistic Regression with Interactions3分鐘

Demo: Fitting a Logistic Regression Model with Interactions2分鐘

Common Issues3分鐘

2 個閱讀材料

Read About It1分鐘

Summary: Correlation and Regression1分鐘

30 個練習

Question 5.012分鐘

Question 5.02-5.032分鐘

Practice: Exploring Correlations (Example)10分鐘

Practice: Exploring Correlations (Case Study)10分鐘

Question 5.051分鐘

Practice: Fitting a Simple Linear Regression Model10分鐘

Question 5.061分鐘

Practice: Exploring Least Squares10分鐘

Practice: Visualizing Regression with Anscombe's Quartet10分鐘

Practice: Interpreting Regression Analysis Results10分鐘

Practice: Fitting Polynomial Models10分鐘

Question 5.081分鐘

Practice: Comparing Simple Linear and Multiple Linear Regression Models10分鐘

Question 5.0910分鐘

Practice: Exploring Significant Predictors10分鐘

Question 5.101分鐘

Practice: Identifying Outliers and Influential Observations10分鐘

Question 5.111分鐘

Practice: Fitting a Model with Categorical Predictors10分鐘

Question 5.121分鐘

Practice: Fitting a Model with Interactions10分鐘

Practice: Selecting Variables Using Effect Summary10分鐘

Question 5.141分鐘

Question 5.151分鐘

Practice: Regression Modeling Mini Case Study10分鐘

Question 5.161分鐘

Question 5.172分鐘

Practice: Fitting a Simple Logistic Model for Reaction Time10分鐘

Practice: Fitting a Multiple Logistic Regression Model10分鐘

Practice: Fitting a Logistic Regression Model with Interactions10分鐘

週

週 7

完成時間為 5 小時

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.

完成時間為 5 小時

36 個視頻（總計 148 分鐘）, 2 個閱讀材料, 27 個測驗

36 個視頻

Introduction1分鐘

A View from Industry4分鐘

What is DOE?5分鐘

Conducting Ad Hoc and One-Factor-at-a-Time (OFAT) Experiments5分鐘

Why Use DOE?4分鐘

Terminology of DOE3分鐘

Types of Experimental Designs7分鐘

Designing Factorial Experiments6分鐘

Demo: Designing Full Factorial Experiments5分鐘

Analyzing a Replicated Full Factorial5分鐘

Analyzing an Unreplicated Full Factorial3分鐘

Demo: Analyzing Full Factorial Experiments5分鐘

Summary of Factorial Experiments1分鐘

Screening for Important Effects1分鐘

A Look at Fractional Factorial Designs4分鐘

Demo: Creating 2^k-r Fractional Factorial Designs4分鐘

Custom Screening Designs4分鐘

Demo: Creating Screening Designs in the Custom Designer3分鐘

Introduction to Response Surface Designs2分鐘

Response Surface Designs for Two Factors5分鐘

Analyzing Response Surface Experiments4分鐘

Demo: Designing a Central Composite Design4分鐘

Creating Custom Response Surface Designs2分鐘

Sequential Experimentation4分鐘

Response Surface Summary1分鐘

Introduction to DOE Guidelines4分鐘

Defining the Problem and the Objectives3分鐘

Identifying the Responses1分鐘

Identifying the Factors and Factor Levels4分鐘

Identifying Restrictions and Constraints4分鐘

Preparing to Conduct the Experiment2分鐘

The Anodize Case Study: Part 16分鐘

The Anodize Case Study: Part 23分鐘

Summary1分鐘

Demo: Optimizing Multiple Responses4分鐘

Demo: Simulating Data Using the Prediction Profiler5分鐘

2 個閱讀材料

Read About It1分鐘

Summary: Design of Experiments (DOE)1分鐘

25 個練習

Question 6.01 - 6.021分鐘

Question 6.031分鐘

Question 6.042分鐘

Question 6.052分鐘

Question 6.06 - 6.072分鐘

Question 6.082分鐘

Question 6.09 - 6.122分鐘

Practice: Designing a Full Factorial Experiment10分鐘

Question 6.13 - 6.142分鐘

Question 6.151分鐘

Question 6.161分鐘

Practice: Analyzing a Replicated Full Factorial Experiment10分鐘

Question 6.171分鐘

Question 6.18 - 6.192分鐘

Practice: Designing a Fractional Factorial Experiment10分鐘

Practice: Analyzing a 20-Run Custom Design10分鐘

Question 6.21- 6.22

Question 6.23 - 6.242分鐘

Practice: Analyzing a Custom Central Composite Design10分鐘

Practice: Optimizing the Heck Reaction10分鐘

Question 6.261分鐘

Question 6.27 - 6.282分鐘

Question 6.291分鐘

Question 6.301分鐘

Practice: Optimizing Multiple Responses10分鐘

週

週 8

完成時間為 6 小時

Module 7: Predictive Modeling and Text Mining

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

完成時間為 6 小時

39 個視頻（總計 143 分鐘）, 2 個閱讀材料, 32 個測驗

39 個視頻

Introduction54

Introduction to Predictive Modeling5分鐘

Overfitting and Model Validation8分鐘

Demo: Creating a Validation Column3分鐘

Assessing Model Performance: Prediction Models5分鐘

Demo: Fitting a Multiple Linear Regression Model with Validation2分鐘

Assessing Model Performance: Classification Models3分鐘

Receiver-Operating Characteristic (ROC) Curves4分鐘

Demo: Fitting a Logistic Model with Validation1分鐘

Demo: Changing the Cutoff for Classification3分鐘

Introduction to Decision Trees1分鐘

Classification Trees4分鐘

Demo: Creating a Classification Tree4分鐘

Regression Trees5分鐘

Demo: Fitting a Regression Tree3分鐘

Decision Trees with Validation4分鐘

Demo: Fitting a Decision Tree with Validation3分鐘

Random (Bootstrap) Forests5分鐘

Demo: Variable Selection with a Bootstrap Forest2分鐘

What is a Neural Network?1分鐘

Interpreting Neural Networks3分鐘

Demo: Fitting a Neural Network3分鐘

Predictive Modeling with Neural Networks3分鐘

Demo: Fitting a Neural Model with Two Layers3分鐘

Introduction to Generalized Regression2分鐘

Fitting Models Using Maximum Likelihood3分鐘

Demo: Fitting a Linear Model in Generalized Regression3分鐘

Demo: Variable Selection in Generalized Regression4分鐘

Introduction to Penalized Regression3分鐘

Demo: Fitting a Penalized Regression (Lasso) Model4分鐘

Comparing Predictive Models4分鐘

Demo: Comparing and Selecting Predictive Models4分鐘

Introduction to Text Mining1分鐘

Processing Text Data4分鐘

Curating the Term List2分鐘

Demo: Processing Unstructured Text Data4分鐘

Visualizing and Exploring Text Data3分鐘

Demo: Visualizing and Exploring Text Data4分鐘

Analyzing (Mining) Text Data2分鐘

2 個閱讀材料

Read About It1分鐘

Summary: Predictive Modeling and Text Mining1分鐘

30 個練習

Question 7.011分鐘

Question 7.022分鐘

Question 7.031分鐘

Practice: Fitting a Multiple Linear Regression Model with Validation10分鐘

Practice: Fitting a Logistic Model with Validation10分鐘

Question 7.041分鐘

Practice: Using a Classification Tree for Problem Solving10分鐘

Practice: Identifying Important Variables10分鐘

Question 7.051分鐘

Question 7.061分鐘

Practice: Using a Regression Tree with Validation10分鐘

Practice: Using a Classification Tree with Validation10分鐘

Question 7.071分鐘

Practice: Using Trees to Identify Important Variables10分鐘

Question 7.081分鐘

Practice: Fitting a Simple Neural Network10分鐘

Practice: Fitting a Neural Network for Prediction10分鐘

Practice: Fitting a Neural Network for Classification10分鐘

Question 7.091分鐘

Question 7.101分鐘

Question 7.11 - 7.122分鐘

Practice: Reducing a Model Using Generalized Regression10分鐘

Practice: Fitting a Regression Model using the Lasso10分鐘

Question 7.131分鐘

Practice: Comparing and Selecting Predictive Models10分鐘

Question 7.141分鐘

Question 7.152分鐘

Question 7.161分鐘

Practice: Developing a Term List10分鐘

Practice: Exploring Terms and Phrases in STIPS10分鐘

週

週 9

完成時間為 1 小時

Review Questions and Case Studies

In this module you have an opportunity to test your understanding of what you have learned. In addition, this module will help your prepare for certification if you choose to take the certification exam.

完成時間為 1 小時

2 個練習

Review Questions30分鐘

Case Studies30分鐘

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Statistical Thinking for Industrial Problem Solving, presented by JMP

Statistical Thinking for Industrial Problem Solving, presented by JMP

課程信息

您將學到的內容有

您將獲得的技能

講師

Mia Stephens

Ledi Trutna

提供方

SAS

教學大綱 - 您將從這門課程中學到什麼

週 1

Course Overview

Module 1: Statistical Thinking and Problem Solving

週 2

Module 2A: Exploratory Data Analysis, Part 1

週 3

Module 2B: Exploratory Data Analysis, Part 2

週 4

Module 3: Quality Methods

週 5

Module 4: Decision Making with Data

週 6

Module 5: Correlation and Regression

週 7

Module 6: Design of Experiments (DOE)

週 8

Module 7: Predictive Modeling and Text Mining

週 9

Review Questions and Case Studies

審閱

來自STATISTICAL THINKING FOR INDUSTRIAL PROBLEM SOLVING, PRESENTED BY JMP的熱門評論

常見問題

熱門在線課程

熱門在線專項課程

在線證書

在線學位課程

Coursera

社區

更多

Statistical Thinking for Industrial Problem Solving, presented by JMP

Statistical Thinking for Industrial Problem Solving, presented by JMP

課程信息

您將學到的內容有

您將獲得的技能

講師

Mia Stephens

Ledi Trutna

提供方

SAS

教學大綱 - 您將從這門課程中學到什麼

週 1

Course Overview

Module 1: Statistical Thinking and Problem Solving

週 2

Module 2A: Exploratory Data Analysis, Part 1

週 3

Module 2B: Exploratory Data Analysis, Part 2

週 4

Module 3: Quality Methods

週 5

Module 4: Decision Making with Data

週 6

Module 5: Correlation and Regression

週 7

Module 6: Design of Experiments (DOE)

週 8

Module 7: Predictive Modeling and Text Mining

週 9

Review Questions and Case Studies

審閱

來自STATISTICAL THINKING FOR INDUSTRIAL PROBLEM SOLVING, PRESENTED BY JMP的熱門評論

常見問題

Coursera Footer

熱門在線課程

熱門在線專項課程

在線證書

在線學位課程

Coursera

社區

更多