## 7QC Tools: Scatter Plot

Amrendra RoyIn general after preparing **flow chart** there is a brainstorming session, and the outcome of this brainstorming session is the **fish-bone diagram **which in-turn list down the probable parameters or causes that can affect your quality parameter. At this step all parameters thus collected are only suspects (unless proven guilty!) and their role in affecting the quality parameters needs to be proved in order to held them guilty. In this regard historical data of all suspects (probable parameters or causes) are collected and their effect on the quality parameter is evaluated using **scatter plot**.

*This evaluation can be dome by expert using ANOVA, Regression etc. but a visual tool was required which can tell a shop-floor person that a given parameter is affecting the quality attributes or not? In this regard scatter plot comes handy where you plot a given parameter against the quality attributes.*

In real case scenario, we end-up with huge data base as shown below, where X^{1} to X^{8} represents the process parameters (suspects) and y represents the quality attribute of interest.

By visual inspection of the above data, it becomes difficult to analyze the effect of X on Y, situation becomes worse if data is larger. Hence, *scatter plot is a visual tool that gives qualitative correlation between X and Y*.

Let’s look at the scatter plot of X^{1} and X^{2} *Vs.* Y

X-Axis represents X and Y-axis represents Y. we can see that in scatter plot of X^{1} *Vs.* Y, as the value of X^{1} increases, Y also increases. Whereas in X^{2} *Vs.* Y, there is no apparent correlation. Hence, we can conclude that X^{1} is affecting the Y and there is no effect of X^{2} on Y. We can also quantify the effect by calculating R_{2} values. R2 values can vary from -1 to +1. The values close to +1 indicates strong positive correlation whereas values close to -1 indicates strong negative correlation.

Scatter plot of all X Vs. Y are given below along with R_{2} values.

Looking at the scatter plot given above, any shop-floor person can tell that X^{1}, X^{3} and X^{5} are affecting the Y in positive way whereas, X^{4} and X^{8} are affecting the Y in negative way. Also X^{2} and X^{6} doesn’t have any effect on Y.

Related Blogs

*7QC Tools: Flow Chart, Know Your Process Thoroughly*

__7QC Tools: Fish Bone or Ishikawa Diagram__

__7QC Tools: How to Extract More Information from the Scatter Plot?__

__7QC Tools: How to Draw a Scatter Plot?__

__7QC Tools: Scatter Plot — Caution! Misuse of Statistics!__

__7QC Tools — How to Prioritize Your Work Using Pareto Chart?__

__7QC Tools — How to Interpret a Histogram?__

__7QC Tools — How to Draw a Histogram?__

__7QC Tools — Histogram of Continuous Data__

__7QC Tools — Histogram of Discrete Data__

__Excellent Templates for 7QC tools from ASQ__

__What are Seven QC Tools & How to Remember them?__

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