Graphing the data can be utilized for both historical data already available and when analyzing the data resulting from live data collection activities. Of course, you need to pick the right graphical tool as there are a lot of different ways to plot your data. A number of commonly used graphical tools will be covered here. However, note that if one graph fails to reveal anything useful, try another one.

Read more »»# Category Archives: Understanding Cause and Effect

# Normal Distribution

Continuous distributions describe variables that take values from a continuous range and can be measured with any degree of accuracy. The commonest and the most useful continuous distribution is the normal distribution. The **Normal Distribution** is a symmetrical probability distribution where most results are located in the middle and few are spread on both sides. It has the shape of a bell and can entirely be described by its mean and standard deviation. Read more »»

# Probability Distributions

Most improvement projects and scientific research studies are conducted with sample data rather than with data from an entire population. A **Probability Distribution** is a way to shape the sample data to make predictions and draw conclusions about an entire population. It refers to the frequency at which some events or experiments occur. It helps finding all the possible values a random variable can take between the minimum and maximum statistically possible values. Read more »»

# Descriptive Statistics

Descriptive statistics are methods of describing the characteristics of a data set. It includes calculating things such as the average of the data, its spread and the shape it produces. It involves describing, summarizing and organizing the data so it can be easily understood. Graphical displays are often used along with the quantitative measures to enable clarity of communication. Descriptive statistics helps exploring and making conclusions about the data in order to make more rational decisions. Read more »»

# Relationship Mapping

A **Relationship Map** is a visual display that shows the relationships between individual items. It allows to see and analyze the logical links between the different elements of any situation. A simple example of a relationship map is your network of personal and social relations. Another example is what is called the **Interrelationship Digraph** which is a visual display of the cause and effect relationships involved in a process or problem. Read more »»

# Matrix Diagram

A **Matrix Diagram** is a table that allows sets of data to be compared in order to make better decisions. It displays the existence and strength of relationship between pairs of items of two or more sets. The relationship is then indicated by a number or symbol in each cell where the two items intersect in the matrix. A matrix diagram can be used as part of other decision making tools. Cause and Effect Matrix and Quality Function Deployment are examples of tools that use the matrix diagram. Read more »»

# Fishbone Diagram

Sometimes it is difficult to spot problems and only symptoms will be acted on leaving the real causes intact. This indicates lack of information and poor understanding of the problem and leads usually to a weak solution. A **Fishbone Diagram** is often used to identify and organize the potential causes of a business problem in an easy and understandable format. It is used to identify the sources of process variation which caused the problem to occur. It is called this way because of its shape that looks like a fishbone. It is also called **Ishikawa Diagram** and **Cause and Effect Diagram**. Read more »»

# Scatter Plots

Many situations require the investigating whether a relationship exists between two or more variables. A **Scatter Plot** is a diagram showing whether two variables are correlated or related to each other. It shows patterns in the relationship that cannot be seen by just looking at the data. It is often used as a first step in analyzing and communicating the correlation between pairs of variables before conducting advanced statistical analyses. It works with both continuous and count data.

# SIPOC Mapping

A **SIPOC Map** is a high-level process map that defines the scope of a process and its inputs, outputs, suppliers and customers. It represents the flow of the process and its key elements in a table format. It is widely used in process design and improvement initiatives to identify relevant information before starting a project. SIPOC is an acronym that stands for Suppliers, Inputs, Process, Outputs and Customers. Read more »»

# Histograms and Boxplots

## Histograms:

A **histogram** is a graphical representation of a frequency distribution for numeric data. It is a **bar chart** that is often used as the first step to determine the probability distribution of a data set or a sample. It allows to visually and quickly assess the shape of the distribution, the central tendency, the amount of variation in the data, and the presence of gaps, outliers or unusual data points. Read more »»

# Pareto Analysis

There are many situations where you are asked to decide which problems or causes of a problem should be tackled first. The **Pareto Principle**, which is also referred to as the 80-20 rule, states that roughly 80 percent of the problems or effects come from 20 percent of the causes. It describes a statistical phenomenon that a small number of high values contribute more to the total than a high number of low values. The focus of the **Pareto Analysis** is to identify the “vital few” from the “trivial many” and make it possible to attack the 80 percent of the problems to obtain the maximum benefits.