The scatter plot is one of 7 QC Tools which can help to analize relationship between two variable.
To check the dependence / impact of change in one variable on other variable.
One variable plotted on horizontal axis and other variable is plotted on Vertical axis.
by the plotting of these two variable in this kind, the pattern of intersecting points of these variables can show relationship pattern between that variables.
Scatter plot diagram is used to validate the root cause of identified problems.
Generally 50 to 100 no. of paired samples data are collected to plot the scatter plot.
Interpretation of the scatter plot:
6 no of possibilities in scatter plot to interpretation of the plot.
Correlation between two variables can be accessed in below outcome:
To check the dependence / impact of change in one variable on other variable.
One variable plotted on horizontal axis and other variable is plotted on Vertical axis.
by the plotting of these two variable in this kind, the pattern of intersecting points of these variables can show relationship pattern between that variables.
Scatter plot diagram is used to validate the root cause of identified problems.
Generally 50 to 100 no. of paired samples data are collected to plot the scatter plot.
Interpretation of the scatter plot:
6 no of possibilities in scatter plot to interpretation of the plot.
Correlation between two variables can be accessed in below outcome:
- Strong Positive = Y-Value increase by increasing X-Value
- Weak Positive = Y-Value increase by increasing X-Value (Slightly)
- Strong Negative = Y-Value decrease by increasing X-Value
- Weak Negative = Y-Value decrease by increasing X-Value (Slightly)
- complex = Y Values are related to the X- Value but not easily determined
- No Relation = There is No relation between Y-Value and X- Value.