0:00 Classifying and Collecting Data 0:37 Classifying Data 4:34 Qualitative and Quantative Data 8:12 Continuous and Discrete Data 18:22 Types of Data Collection 23:08 Contents of a Data Collection Plan 29:04 Data Sources, Sampling, and Frequency 34:59 Data Collection Best Practices 39:40 Avoiding Data Collection Problems 45:22 Using Information Technology for Data Collection 51:07 Using Surveys for Data Collection 57:10 Using Interviews for Data Collection 1:02:15 Using Checklists for Data Collection 1:07:21 Six Sigma Measurement System Analysis 1:12:44 Precision and Accuracy of the Measurement System 1:17:46 Concepts Related to Measuring Accuracy 1:20:11 Assessing Bias 1:25:08 Linearity of a Measurement System 1:28:24 Assessing Linearity 1:33:03 Stability of a Measurement System 1:37:09 Repeatability and Reproducibility 1:40:45 GR&R Study 1:47:43 GR&R and Total Variation 1:52:32 Lean Tools and FMEA 1:52:58 Common Lean Tools 1:58:07 5S for Workplace Organization 2:05:20 Value Analysis in Six Sigma 2:11:09 Identifying Types of Waste 2:18:17 Value Stream Analysis 2:25:09 Introduction to FMEA 2:30:33 Types of FMEA 2:35:01 Severity, Opportunity, and Detection 2:40:45 Using the Risk Priority Number 2:44:48 Using FMEA Worksheets 2:49:56 Data Analysis and Root Cause Analysis 2:50:27 Variables and Probability Distributions 2:53:37 Introduction to Normal Distribution 2:56:15 Introduction to Binomial Distribution 2:59:18 Skewed and Bimodal Curves 3:03:09 Common and Special Cause Variations 3:10:35 Introduction to Root Cause Analysis 3:14:17 5 Whys Analysis 3:21:16 Process Mapping 3:27:05 Process Map Symbols 3:32:59 Relational Matrix Charts 3:38:21 Force-field Analysis 3:44:12 Correlation, Regression, and Hypothesis Testing 3:44:35 Correlation Basics 3:47:50 Scatter Diagrams and Correlation Analysis 3:52:14 Correlation Coefficient 3:55:44 Causation and the Significance of Correlation 4:02:29 Basics of Regression Analysis 4:05:32 Predicting Outcomes with Regression Analysis 4:12:39 Introduction to Hypothesis Testing 4:16:39 Null and Alternative Hypotheses 4:20:33 Type I and Type II Errors 4:24:51 One- versus Two-tailed Hypothesis Tests 4:30:10 Power of a Test 4:34:16 The p-value for a Hypothesis Test 4:39:19 Kaizen and Six Sigma 4:39:46 Six Sigma Techniques for Improvement 4:47:32 The Kaizen Process 4:55:14 Conducting a Kaizen Blitz 5:03:04 Applying Kaizen in Your Organization 5:09:14 Introduction to PDCA 5:12:28 Steps in the PDCA Cycle 5:16:46 Six Sigma and Cost-Benefit Analysis 5:23:17 Identifying Benefits 5:27:48 Identifying Costs 5:31:33 Conducting a Cost-Benefit Analysis 5:38:09 Six Sigma Control Tools and Documentation 5:38:36 Using Control Plans for Six Sigma Projects 5:43:51 Creating a Control Plan 5:50:16 Control Plan Hand-off 5:53:06 Statistical Process Control in Six Sigma 5:56:56 Introduction to Control Charts 6:02:07 Types of Control Charts 6:08:50 Choosing a Control Chart 6:13:27 Creating an Xbar-R Chart 6:18:52 Interpreting Data Trends in Control Charts 6:24:53 Documentation for Project Control 6:30:06 Types of Control Documents
On 4:38:16 is mentioned that we reject the Null due to the P-Value of 0.064 being greater than the confidence level of 0.05. Shouldn't this Fail to Reject the Null. The P Value is greater, indicating that there isn't enough evidence to Reject the Null. Maybe I'm hearing this wrong.
passed the test 90/100 in 10 hours! I was honestly a little disappointed on the questions I got wrong I know I could have gotten 95 or a 100. Questions were kinda vague kinda questionable what was the right answer.
@@Chuck.Mast3r used a few different sources. Also studying exam questions is a good way to pass the test. Just to get an idea how and what kind questions you can expect.
0:00 Classifying and Collecting Data
0:37 Classifying Data
4:34 Qualitative and Quantative Data
8:12 Continuous and Discrete Data
18:22 Types of Data Collection
23:08 Contents of a Data Collection Plan
29:04 Data Sources, Sampling, and Frequency
34:59 Data Collection Best Practices
39:40 Avoiding Data Collection Problems
45:22 Using Information Technology for Data Collection
51:07 Using Surveys for Data Collection
57:10 Using Interviews for Data Collection
1:02:15 Using Checklists for Data Collection
1:07:21 Six Sigma Measurement System Analysis
1:12:44 Precision and Accuracy of the Measurement System
1:17:46 Concepts Related to Measuring Accuracy
1:20:11 Assessing Bias
1:25:08 Linearity of a Measurement System
1:28:24 Assessing Linearity
1:33:03 Stability of a Measurement System
1:37:09 Repeatability and Reproducibility
1:40:45 GR&R Study
1:47:43 GR&R and Total Variation
1:52:32 Lean Tools and FMEA
1:52:58 Common Lean Tools
1:58:07 5S for Workplace Organization
2:05:20 Value Analysis in Six Sigma
2:11:09 Identifying Types of Waste
2:18:17 Value Stream Analysis
2:25:09 Introduction to FMEA
2:30:33 Types of FMEA
2:35:01 Severity, Opportunity, and Detection
2:40:45 Using the Risk Priority Number
2:44:48 Using FMEA Worksheets
2:49:56 Data Analysis and Root Cause Analysis
2:50:27 Variables and Probability Distributions
2:53:37 Introduction to Normal Distribution
2:56:15 Introduction to Binomial Distribution
2:59:18 Skewed and Bimodal Curves
3:03:09 Common and Special Cause Variations
3:10:35 Introduction to Root Cause Analysis
3:14:17 5 Whys Analysis
3:21:16 Process Mapping
3:27:05 Process Map Symbols
3:32:59 Relational Matrix Charts
3:38:21 Force-field Analysis
3:44:12 Correlation, Regression, and Hypothesis Testing
3:44:35 Correlation Basics
3:47:50 Scatter Diagrams and Correlation Analysis
3:52:14 Correlation Coefficient
3:55:44 Causation and the Significance of Correlation
4:02:29 Basics of Regression Analysis
4:05:32 Predicting Outcomes with Regression Analysis
4:12:39 Introduction to Hypothesis Testing
4:16:39 Null and Alternative Hypotheses
4:20:33 Type I and Type II Errors
4:24:51 One- versus Two-tailed Hypothesis Tests
4:30:10 Power of a Test
4:34:16 The p-value for a Hypothesis Test
4:39:19 Kaizen and Six Sigma
4:39:46 Six Sigma Techniques for Improvement
4:47:32 The Kaizen Process
4:55:14 Conducting a Kaizen Blitz
5:03:04 Applying Kaizen in Your Organization
5:09:14 Introduction to PDCA
5:12:28 Steps in the PDCA Cycle
5:16:46 Six Sigma and Cost-Benefit Analysis
5:23:17 Identifying Benefits
5:27:48 Identifying Costs
5:31:33 Conducting a Cost-Benefit Analysis
5:38:09 Six Sigma Control Tools and Documentation
5:38:36 Using Control Plans for Six Sigma Projects
5:43:51 Creating a Control Plan
5:50:16 Control Plan Hand-off
5:53:06 Statistical Process Control in Six Sigma
5:56:56 Introduction to Control Charts
6:02:07 Types of Control Charts
6:08:50 Choosing a Control Chart
6:13:27 Creating an Xbar-R Chart
6:18:52 Interpreting Data Trends in Control Charts
6:24:53 Documentation for Project Control
6:30:06 Types of Control Documents
Thank you very much for making playtime to this course
On 4:38:16 is mentioned that we reject the Null due to the P-Value of 0.064 being greater than the confidence level of 0.05. Shouldn't this Fail to Reject the Null. The P Value is greater, indicating that there isn't enough evidence to Reject the Null. Maybe I'm hearing this wrong.
Can you activate closed caption.
Please provide the class slide pdf
subtitle please
10:13
Male vs Female Gender Difference.
RESPECT !!!!!!
Rodriguez Robert Anderson Matthew Thompson Jennifer
passed the test 90/100 in 10 hours! I was honestly a little disappointed on the questions I got wrong I know I could have gotten 95 or a 100. Questions were kinda vague kinda questionable what was the right answer.
Did you mostly use this training?
@@Chuck.Mast3r used a few different sources. Also studying exam questions is a good way to pass the test. Just to get an idea how and what kind questions you can expect.
@@LandsoulFFXI where did you take the test? And where did you get the practice exams to study?
My questions Same as Edward
Where did you get the practice test?
Thomas Cynthia Lopez Kimberly Thompson Frank
Harris Cynthia Jackson Amy Perez Anthony