Table of contents
- 1. Intro to Stats and Collecting Data24m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables1h 16m
- 6. Normal Distribution and Continuous Random Variables58m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 3m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 5m
- 9. Hypothesis Testing for One Sample1h 1m
- 10. Hypothesis Testing for Two Samples2h 8m
- 11. Correlation48m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
1. Intro to Stats and Collecting Data
Intro to Stats
Problem 14.CQQ.3
Textbook Question
Identify three specific criteria for determining when a process is out of statistical control.

1
Understand the concept of statistical control: A process is in statistical control when it operates with only common cause variation, which is inherent to the process. Special cause variation, on the other hand, indicates that the process is out of control.
Learn about control charts: Control charts are tools used to determine whether a process is in statistical control. They plot data points over time and include a center line (mean), an upper control limit (UCL), and a lower control limit (LCL).
Criterion 1 - Points outside control limits: Identify if any data points fall outside the upper or lower control limits. This is a strong indication that the process is out of control due to special cause variation.
Criterion 2 - Run tests: Look for patterns within the control limits, such as a run of seven or more points all above or below the center line. This suggests a non-random pattern and potential special cause variation.
Criterion 3 - Cycles or trends: Detect any systematic patterns, such as cycles or trends, within the data points. These patterns can indicate that the process is being influenced by factors other than random variation, suggesting it is out of control.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Control Charts
Control charts are a statistical tool used to monitor whether a process is in a state of control. They display data points over time and include a central line for the average, an upper line for the upper control limit, and a lower line for the lower control limit. A process is considered out of control if data points fall outside these control limits.
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Common and Special Causes of Variation
In statistical process control, variations in a process can be attributed to common causes, which are inherent to the process, or special causes, which are unusual or unexpected. Identifying special causes is crucial for determining when a process is out of control, as they indicate that something specific and correctable has affected the process.
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Run Rules
Run rules are criteria used to detect non-random patterns in control charts, indicating a process may be out of control. Examples include a sequence of points all above or below the central line, or a series of points trending upward or downward. These patterns suggest systematic changes in the process that need investigation.
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