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- 1. ABB Basic QualityTools Series Scatter Diagram Graphical presentation of the data to identify patterns or relationship © ABB Group 9AKK105151D0107 15 July 2010, Slide1
- 2. Scatter Diagram -Content What is it for? • To understand the behaviour of a process. • To see if two factors have a relationship. • To visually show correlation between two factors. Where could I use it? • When collecting information on the possible causes of a problem. • When a relationship between two factors is suspected. • When the actual type and degree of a known relationship is required. How do I use it? • Identify the purpose. • Determine the two factors to compare. • Identify the measures. • Collect the data. • Plot the Scatter Diagram. • Interpret the diagram. • Take action. Risks and how to avoid them Effect of Wort Temp on Strength 1.010 1.005 1.000 0.995 0.990 0.985 0.980 9.95 10.00 10.05 10.10 10.15 10.20 Wort Temperature Final Spec Gravity Final Spec Gravity 10 0 2 4 6 8 0 10 20 30 40 50 60 Average speed Accidents in day Example © ABB Group 9AKK105151D0107 15 July 2010, Slide2
- 3. Scatter Diagram -What is it for? Uses of this tool: • To understand the behaviour of a process. • To determine if there is a relationship between two factors. • To visually demonstrate the correlation between two related factors. • To determine where there may be a cause and effect relationship. Expected Benefits: • Verification that there is or is not a relationship between 2 factors. • Identifying an independent controlling factor for a dependent factor. © ABB Group 9AKK105151D0107 15 July 2010, Slide3
- 4. Scatter Diagram -Where could I use it? Background: • Sometimes two separate things appear to change together and there may be suspicion that they are related somehow. The Scatter Diagram visually shows how well correlated they are. • The Japanese guru Kaoru Ishikawa included Scatter Diagrams as one of his 7 basic tools. Uses: • Use it during the analysis phase to understand the behaviour of a process and how a pair of variables change relative to one another (correlation). • Use it to provide an input to cause and effect analysis. • After improvement, to find out how much the behaviour of the process has changed. © ABB Group 9AKK105151D0107 15 July 2010, Slide4
- 5. Scatter Diagram -How do I use it? Procedure and Guidance Notes Determine the two factors to compare • Select the two factors which you are going to compare. • In a complex situation where there are many factors, you may do a number of comparisons between separate pairs of variables. • Identify the measurement units for the factors. One of these measures may well be a factor that you are trying to change, for example ‘road traffic accidents’. Other measures may have suspected relationships, e.g. ‘traffic speed’. Identify the measures • Select the measurement units values of the factors • It must be possible to measure both factors at the same time, such that they form pairs of values that can be plotted as single points on the Scatter Diagram. The factors must both be variables - i.e. able to be measured on a continuous scale (such as speed) rather than attributes (such as colour). CCoolllleecctt tthhee ddaattaa • Collect measurements of the dependent factor for the selected values of the independent. • Alternatively collect 50-100 pairs of measures for the 2 factors. Take care to control any other factors that could also have a relationship. Pay particular care when measuring human factors as measuring itself can cause an effect. Plot the Scatter Diagram • Plot the collected data on an x y graph. • This can be done using a spreadsheet such as Microsoft Excel. Select the scale of the axes to give maximum spread of the data. This could mean having different scales for each and/or having the axis commence at a non-zero point. IInntteerrpprreett • Look for a correlation between the 2 factors. • The tighter the dots follow an imagined line, the closer is the correlation. • Note that correlation does not prove cause-and-effect. Correlation Coefficient can be calculated, as can a line of best fit. These are beyond the scope of this toolkit description. See types of correlation on next slide. Identify the purpose • Clarify what you are trying to achieve by using the Scatter Diagram. • Be clear about what is included and what is not included in the analysis. For example, ‘Reduce all road accidents within the residential areas of the town.’ TTaakkee aaccttiioonn • Act on your findings. For example, do further trials to verify whether there is a real causal relationship between the two factors. © ABB Group 9AKK105151D0107 15 July 2010, Slide5
- 6. Scatter Diagram -How do I use it? - Correlation Degrees of correlation: None Low High Perfect Types of correlation: Positive Negative Curved Partial © ABB Group 9AKK105151D0107 15 July 2010, Slide6
- 7. Scatter Diagram -Risks and how to avoid them Risks : • Assuming that because two factors are well correlated there is a cause-and-effect relationship between them. • Dots are clumped in one area of scatter diagram. • Data needs to be plotted at the same point - therefore the ‘weight’ of the numbers of points is lost. • There is a difference in the sources of the data - this may have a relevance. Steps to avoid them : • Understand the difference between correlation and causation. At best, see correlation as indication of possible cause that will need further testing to prove any actual causal relationship. • Chose the axis scales carefully so that maximum spread is achieved. (e.g. use values close to the minimum and maximum values for the start and end points of each axis. • Apply concentric circles to these points to indicate the ’weight’ • Plot the different sources using different symbols (See also Sampling / Stratification) © ABB Group 9AKK105151D0107 15 July 2010, Slide7
- 8. Scatter Diagram -Example Do trials in three areas with speed limits at 20, 25 and 30. 10 10 0 2 4 6 8 0 5 10 15 Vehicles per minute Accidents in day 1. Identify purpose Understand factors that may lead to road accidents 5. Plot Scatter Diagram 6. Interpret 2. Identify two factors 3. Identify measures Speed = Average Speed Density = Vehicles per minute 0 2 4 6 8 0 10 20 30 40 50 60 Average speed Accidents in day 4. Collect data Average Speed Vehicles per minute Accidents in day 15.40 0 1 43.40 3 6 31.00 2 2 27.40 1 1 32.80 1 3 40.20 3 5 34.20 6 4 8.40 0 1 20.80 1 1 33.40 3 3 32.00 1 2 17.00 0 1 26.60 1 1 15.40 1 2 29.40 2 2 Close correlation between speed and accidents when speed is above about 25 Weak correlation between traffic density and accidents 7. Take action Traffic speed and density © ABB Group 9AKK105151D0107 15 July 2010, Slide8