What is a Scatter Diagram in 7 QC Tools?
→ Scatter Diagram is used to study and identify the possible relationship between two variables.→ It is also used to validate the relationship between cause and effects and it is also known as the validation tool.
→ Scatter Chart in 7 QC Tools is a graph in which the values of two variables are plotted along two axes of the graph, the pattern of the resulting points will say the correlation.
→ We use this chart to find out the relation between cause and its effect by using cause and effect diagram.
→ This tool is commonly used in the analyze phase in the Six Sigma Methodology.
Scatter Plot Examples
→ Refer below the relations of two variables that we can found in our real life.- Weight and Height of a man.
- Hardness and carbon content in the product.
- Visual Inspection mistakes and Illumination levels.
- Child’s height and Father’s height.
- Curing Temperature and Curing Time.
- Advertising and sales.
What is a scatter diagram used for?
- It is used for validation of two different variable
- It is also used for checking the trend with respect to time
- The Scatter_diagram is used to confirm a hypothesis testing between two variables.
How to draw a Scatter Diagram?
→ Refer below four steps for Making a Scatter_Graph.
- Data Collection
- Choose Independent and Dependent variables.
- Construct the Graph and add the titles & trend line.
- Interpret the Graph
Step 1. Data Collection:
→ Now we are taking one example to understand how to make a chart?→ In this example, we are taking 50 readings of different curing temperatures on different curing times for a product manufactured on the thermosetting press. we want to find out the relation between curing time and curing temperature.
→ We have to find is any correlation is present or not between curing temperature and curing time.
→ If we have more data sample then it will give a more precise result.
Step 2. Choose Independent and Dependent Variables:
→ The dependent variable is usually plotted along the vertical axis i.e. in Y-axis and it is called a measured parameter.→ The independent variable is usually plotted along the horizontal axis i.e. in X-axis and it is called a control parameter.
→ In this case, we are taking heating temperature as an independent variable on the x-axis, and curing time is dependent on heating temp. so we mentioned it on the y-axis.
Step 3. Construct the Graph and add the titles & trend line:
→ Now based on recorded data construct a graph and add a suitable title, horizontal axis name, vertical axis name, and make trend line.Step 4. Interpret the Graph
→ We will interpret the chart based on the trend line.Types of Correlation in Scatter Diagram in 7 QC Tools:
→ There are many different types of correlation found between the Independent and Dependent variables which are mentioned below with pictorial representation.→ Mainly three relations available between two variables we can say that Strong, Moderate, and No Relation.
→ A strong positive correlation means it is a clearly visible upward trend from left to right, a strong negative correlation means it is a clearly visible downward trend from left to right.
→ eg. In positive relation, as the value of x increases, the value of y will also increase we can say that the slope of the straight line drawn along the data points will go up and the pattern will resemble the straight line.
→ For example, in the summer season the temperature increase, icecream sales will also increase.
→ A negative correlation, as the value of x increases, the value of y will decrease and the slope of a straight line drawn along the data points will go down.
→ For example, in the summer season the temperature increase, the sales of winter coats decrease.
→ A weak correlation means it is less clear that the relationship is either positive or negative?
→ No correlation means neither positive nor negative relation and indicates the independent variable does not affect the dependent variable.
What are the 3 types of scatter plots?
→ There are main three types are mentioned below.
- Positive
- Negative
- Neutral
⇢ (1) Strong Positive
⇢ (2) Moderate Positive
⇢ (3) Weak Positive
⇢ (4). Strong Negative
⇢ (5). Moderate Negative
⇢ (6). Weak Negative
⇢ (7). Random Pattern
Benefits of Scatter Diagram:
→ It is beneficial to confirm a hypothesis (assumption) between two variables that are related or not.→ Provide both visual and statistical means to test the strength of a potential relationship.
→ It is a very good validation tool.
→ Used for proving the relation between cause and effect.
→ Plotting the diagram is relatively simple.
Limitation of Scatter Plot:
→ It does not show you the quantitative measure of the relationship between the variable.→ This chart does not show you the relationship for more than two variables at a time.
👉 Also Read:
2. Cause & Effect Diagram (Fishbone or Ishikawa)
👉 For a regular update :
➨ Join us (Telegram Group)
➨ Join us (WhatsApp Group)
👉 See Also:
Great presentation
ReplyDeleteThank you for your kind word
Deleteyou know , you are amazing
ReplyDeleteThanks for your kind words
DeleteVery good information for us
ReplyDeleteThanks for your kind words.
DeleteThanks so much
ReplyDeleteYou are welcome and happy learning!!!
DeletePost a Comment