Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 3m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 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 14.2.1
Textbook Question
Minting Quarters Specifications for a quarter require that it be 8.33% nickel and 91.67% copper; it must weigh 5.670 g and have a diameter of 24.26 mm and a thickness of 1.75 mm; and it must have 119 reeds on the edge. A quarter is considered to be defective if it deviates substantially from those specifications. A production process is monitored, defects are recorded and the accompanying control chart is obtained. Does this process appear to be within statistical control? If not, identify any out-of-control criteria that are satisfied. Is the manufacturing process deteriorating?
[IMAGE]

1
Step 1: Understand the problem. The question asks whether the production process for minting quarters is within statistical control. This involves analyzing the control chart provided and identifying any signs of the process being out of control.
Step 2: Review the criteria for a process being out of control. Common criteria include: (1) a single point outside the control limits, (2) a run of consecutive points on one side of the centerline, (3) a trend of points consistently increasing or decreasing, or (4) unusual patterns such as cycles or clusters.
Step 3: Examine the control chart. Look for any points that fall outside the upper or lower control limits. These points indicate that the process may be out of control.
Step 4: Check for patterns or trends. Identify if there are consecutive points above or below the centerline, or if there is a consistent upward or downward trend. These patterns can suggest that the process is deteriorating or experiencing systematic issues.
Step 5: Summarize findings. Based on the analysis of the control chart, determine whether the process is within control or not. If any out-of-control criteria are met, describe them and assess whether they indicate a deteriorating manufacturing process.

This video solution was recommended by our tutors as helpful for the problem above
Video duration:
4mPlay a video:
Was this helpful?
Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Statistical Control
Statistical control refers to a process being stable and predictable over time, where variations are due to common causes rather than special causes. Control charts are used to monitor process behavior, indicating whether a process is in control (stable) or out of control (unstable). A process is considered in control if all data points fall within control limits, which are typically set at ±3 standard deviations from the mean.
Recommended video:
Guided course
Parameters vs. Statistics
Defect Criteria
Defect criteria are specific thresholds or standards that determine whether a product meets quality specifications. In the context of manufacturing, a product is deemed defective if it deviates significantly from established specifications, such as weight, dimensions, or material composition. Identifying these criteria helps in assessing the quality of the production process and determining if corrective actions are necessary.
Recommended video:
Guided course
Intro to Random Variables & Probability Distributions
Control Chart Analysis
Control chart analysis involves examining graphical representations of process data over time to identify trends, shifts, or outliers. This analysis helps in detecting variations that may indicate a deterioration in the manufacturing process. By evaluating the control chart, one can determine if the process remains stable or if there are signs of increasing defects, which may suggest a need for process improvement.
Recommended video:
Creating Pie Charts
Watch next
Master Introduction to Statistics Channel with a bite sized video explanation from Patrick
Start learning