## 7QC Tools — Histogram of Continuous Data

Let’s consider the percentage yield of a process, which ranges from 74 to 94. This is a case of continuous data.

As we did for discrete data, we have constructed the histogram of the yield data by dividing the yield into some sub-classes followed by putting the data into the class it belongs.

Note:

Unlike discrete data, the bars of the present histogram are touching each other as this is a case of continuous data.

Above histogram tells us that the maximum data is clustered within 78-84. Looking at the graph, it appears that the batches with yield > 88 are outliers! but it’s true. What we should do to improve the process?

What we can do it to compare the process with yield range of 74-82 with the process having yield range of 88-94 and find out the difference.

Hence, histogram gave a direction for continuous improvement.

Let’s go a step ahead and plot the customer’s specification (LSL & USL) along with the histogram as shown below. This gives you the idea about process capability and outliers.

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: Scatter Plot

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 Discrete Data

7QC tools — Check List

Excellent Templates for 7QC tools from ASQ

What are Seven QC Tools & How to Remember them?

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## 7QC Tools — Histogram of Discrete Data

Histogram is a pictorial view of the data set, it is like a portrait of your data. It tells you how your data looks like, where your most of the data is clustered (whether it is the mean or median is the true measure of the central tendency). In short it tells you about the distribution of the data set.

Histogram divides the data set into small sub-units, called as “classes”. This is followed by arranging data according to the class it belongs. In this way we have “class-range” along with their frequencies (i.e. how many data points are there in that class). This is followed by plotting a bar-graph of class Vs frequency, which is known as histogram.

For example

In the check list example we have collected the data about the Reason for failure (= class) and number of defects because of that reason (= frequency).

Now, if we plot the bar graph of the above data, we will get a histogram as shown below, it appears that defects due to reason C, D and G is more prominent and these three requires immediate attention.

Note:

The above data set is a discrete variable hence, the  bars of the histogram are not touching each other.

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: Scatter Plot

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 — Check List

Excellent Templates for 7QC tools from ASQ

What are Seven QC Tools & How to Remember them?

Kindly do provide feedback for continuous improvement

## 7QC tools — Check List

Check list is a method of data collection in a tabular or graphical form. We can collect historical data, make a format for new data collection etc.

In summary we need to make a check list in the form of tabular or graphical form (user friendly format) so that the data collection becomes easy even for shop-floor people.

For example

Check sheet for collecting the data of average temperature for the month of July, 2016.

Check sheet for collecting the data about type of defects in production

Check sheet for collecting the data about type of defects in production in two shifts

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: Scatter Plot

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?

Kindly do provide feedback for continuous improvement

## What are Seven QC Tools & How to Remember them?

Understanding and using hard-core statistics for continuous improvement is an issue with the shop-floor people. In order to overcome this issue it was felt necessary to present statistics in graphical forms so that everyone can understand it.

The 7QC tools made the quality control more simpler so that it could be comprehended easily by all. Now statistics is not a prerogative of some experts in the company. It could easily be percolated down the ranks, irrespective whether someone has a statistical background or not.

7QC tools is a collection of statistical tools which need not to be applied in a particular sequence. However, to understand and remember it we need to connect them with each other.

1. Flow chart
2. Cause & Effect diagram
3. Control charts
4. Check list
5. Histogram
6. Pareto Chart
7. Scatter Plot

One can easily remember the list by using following relationship between the above tools (you can develop some other relationship).

If you want to remember 7QC tools then remember these sequence of events used in continuous improvement.

For starting any continuous improvement program, the first step is about defining the problem (quality characteristic ‘Y’ to be addressed). Once we define the problem, we need to understand the process in-depth using Process Flow Diagram to find the problem areas and non-value adding steps.

From the process flow diagram, find the probable sources of variations (X)  affecting the desired output (Y) using Cause & Effect Diagram.

Once we have identified the probable cause (X), then start monitoring ‘X’ and ‘Y’ using proper Control Charts. This will drop some of the ‘X’s’ came from the cause and effect diagram. Make note of ‘X’ that really affects the ‘Y’.

Once you have real ‘X’ that can affect ‘Y’ then prepare a plan for data collection using Check List to support the cause and effect relationship.

Data thus collected using check list is then arranged in graphical form using Histogram to have a quantitative pictorial view of the effect of ‘X’.

The bars of the histogram constructed above is then re-arranged in descending order to give Pareto Chart. This arranges the causes (X) in descending order of their effect on ‘Y’. Take the list of ‘X’ (usually top 3) having prominent effect on ‘Y’ for continuous improvement.

Finally show a quantitative relationship between top three ‘X’ and ‘Y’ using Scatter Plot in laboratory or by collecting more data from the plant and propose the improvement strategy by providing best conditions for ‘X’ so that ‘Y’ remains within the desired limits.

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: Scatter Plot

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

7QC tools — Check List

Excellent Templates for 7QC tools from ASQ

Kindly do provide feedback for continuous improvement