Graphical Methods Flashcards
Scatter Diagram
- Provides relationship between two variables, and provides a visual correlation coefficient.
Why would you guys Scatter Analysis and Scatter Plots?
Scatter Analysis is used when you need to compare two data sets against each other to see if there is a relationship.
Scatter Plots are a way of visualizing the relationship; by plotting the data points you get a scattering of points on a graph.
Scatter Diagrams are used to show the “cause and effect” relationship between two kinds of data, and to provide more useful information about a production process
The analysis comes in when trying to discern what kind of pattern, if any, is present, and what that pattern means.
It is this kind of analysis we are talking about when we are tying to get at the roof cause of an issue.
Specific instances of when to utilize Scatter Diagrams
- Paris of numerical figures are present
- Dependent variables have multiple value for each figure associated with the independent variable
- Defining if there is a relationship between two variables
What kind of data should you use on Scatter Analysis?
- Continuous Data
- Lets you measure things deeply on an infinite set
Scatter Plots and Correlation
- Scatter Plots only show correlation. They do not prove causation.
- The example often used is shark attacks and ice cream sales. There may be a correlation between the two, but ice cream does not cause shark attacks — the heat of the day does. In other words, more people are in the water on hot days equaling more shark attacks, and more people buy ice cream on hot days
Histogram
- Bar chart showing the frequency of an outcome
- Use to visualize what’s going on
- Can reflect the voice of the process
- Useful in evaluating the shape of the data
Some questions we can to evaluate when interpreting a histogram:
- How many peaks are there?
- Are there outliers?
- Does it look approximately symmetrical and bell-shaped?
- If not, the process being reflected is not a normal distribution
Bell-Shaped Histogram
- If there is a bell shape, your data is normally distributed and hence, no variation (or influence from other factors like the 6Ms)
- Method
- Mother Nature
- Man/People
- Measurement
- Machines
- Materials
Spike Histogram
- If there are multiple spikes in the chart, there is likely variation in the process
- Variation=lack of consistency
Even Histogram
- If all of the bars are at the same level it’s not likely that we are measuring the process in the correct manner
Doing statistical analysis usually involves the following:
- Measuring the central tendency
- Mean, Median, Mode
- Measure of the variation
- Inconsistency
Create a Histogram
- Get Data
- Use continuous data from a frequency distribution check sheet
- Order it and assign categories
- Create a Bar Chart preserving counts and categories
Steam and Left Plot
- Also known as Steam Plots
- Technique to categorize either continuous or discrete values.
- Used to organize data as they are collected
- Methods for showing frequency with which certain classes of values occur.
- Organize data visually and will be able to interpret data and draw conclusions using the plot
- Offers a quick way for simultaneously sorting and displaying data sets where each number in the data set is divided into two parts:
- Stem
- All numbers except the last digit
- Leaf
- Only the last digit
- Stem
Example: The numbers 38 and 52, the steams are 3 and 5, while the leaves are 8 and 2.
Uses of a Stem and Leaf Plot
- Effective way to organize the data. A steam and left plot looks something like a bar graph
- Shows data in an organized way, so it can be analyzed easily
- Organizes data so it is easy to compute the median, mode, and quartiles
- Easy to compare different sets of data together at the same time.
Fishbone Diagram
aka
Cause and Effect Diagram
aka
Ishikawa Diagram
- Pictorial diagram showing possible causes (process inputs) for a given effect (process outputs)
- In other words, it is a visual representation used to find the cause(s) of a specific problem
- Commonly used in brainstorming and the “open” phase of the root cause analysis
When and Why to use the Cause and Effect Diagram
-
When
- The problem has multiple probable causes
- To identify the possible root causes for an effect
- Identify and sort interaction among the factors on an effect
- To initiate appropriate corrective actions for existing problems
-
Why
- It is a basic step to study a problem/issue to determine the root cause
- To study all the probable causes of why a process is beginning to have a problem or breakdowns
- Need to identify areas for data collection for further study
How to develop a Cause and Effect Diagram
- Identify the problem
- Determine the effect or problem
- Identify major causes contributing to the effect or problem
- Man/People
- Methods
- Machines
- Materials
- Measurements
- Environment
- Identify sub causes
- Analyze the diagram