Scatter Diagram
A scatter diagram is a graph that plots pairs of numerical data, with one variable on each axis, to look for a relationship or correlation between the two variables.
Explanation
Scatter diagrams are one of the seven basic quality tools and are used in Control Quality to investigate potential relationships between two variables. Each data point represents a pair of values, and the pattern of points reveals whether a correlation exists. A positive correlation shows both variables increasing together, a negative correlation shows one decreasing as the other increases, and no correlation shows no discernible pattern.\n\nIn quality management, scatter diagrams help identify whether changes in one factor affect another. For example, a team might plot the number of code reviews against the number of defects found in testing to determine whether more reviews lead to fewer defects. The diagram might reveal a strong negative correlation, supporting the decision to increase code review activities.\n\nIt is important to note that correlation does not imply causation. A scatter diagram can show that two variables tend to move together, but it does not prove that one causes the other. Additional analysis, such as root cause analysis or designed experiments, may be needed to establish a causal relationship. The strength and direction of the correlation can be quantified using a correlation coefficient.
Key Points
- •One of the seven basic quality tools
- •Plots paired data to reveal relationships between two variables
- •Can show positive correlation, negative correlation, or no correlation
- •Correlation does not imply causation
Exam Tip
If the exam asks about the relationship between two variables, a scatter diagram is the correct tool. Remember that finding a correlation does not prove one variable causes the other.
Frequently Asked Questions
Related Topics
Control Quality
Control Quality is the process of monitoring and recording the results of executing quality management activities to assess performance and ensure project outputs are complete, correct, and meet customer expectations.
Control Charts
A control chart is a graph used to study how a process changes over time, displaying data points plotted against upper and lower control limits to determine whether the process is in statistical control.
Histograms
A histogram is a bar chart that shows the distribution of data by grouping measurements into intervals (bins), revealing the shape, central tendency, and variability of the data.
Root Cause Analysis
Root cause analysis is a technique used to identify the fundamental underlying reason for a variance, defect, or risk, with the goal of eliminating the root cause rather than just treating symptoms.
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