Tag Archives: data

Graphical Analysis


Graphical Analysis

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.

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Data Collection Plan Template

The main reason behind the Data Collection Plan is to provide a focused approach to data collection for any given study or project. It helps specifying the objective of the data collection, what data do we need, how are we going to collect it, and who is going to collect it. The goal is to answer questions such as whether the process is stable and capable, and whether the measurement system is accurate and capable.

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Audit Checklist

An audit checklist is a set of questions that must be answered to verify requirements or standards are being met. It compensates for the limitation of human memory and helps the observer to ensure that nothing is missed or left behind. It enables the observer to better address compliance gaps and provides an opportunity for continuous improvement. Common examples of checklists are: to-do lists, preventive maintenance schedules, safety audit checklists and 5S audit checklists.

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Matrix Diagram Template

A Matrix Diagram is a table that allows sets of data to be compared to understand the relationship between them. It displays the existence and strength of the relationship between pairs of items of the data sets. The relationship is indicated by a number or symbol in each cell where each two items intersect in the matrix. Matrix diagrams can be useful in a wide range of applications from matching requirements with specifications to assigning responsibilities based on competencies.

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Normality Testing in Minitab

Normality Testing

The Normal Distribution is the commonest and the most useful continuous probability distribution. Many statistical tests require that the distribution is normal or nearly normal. Several tools are available to assess the normality of data including: using a histogram to visually explore the data, producing a normal probability plot, and carrying out an Anderson-Darling normality test. All these tools are easy to use in Minitab statistical software. Read more »»

Probability Distributions in Minitab

Probability Distributions

There are different shapes, models and classifications of probability distributions including the ones discussed in the probability distributions article. It is always a good practice to know the distribution of your data before proceeding with your analysis. Once you find the appropriate model, you can then perform your statistical analysis in the right manner. Minitab can be used to find the appropriate probability distribution of your data. Read more »»

Normal Distribution

Normality Test

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

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 in Minitab

Descriptive Statistics

Minitab is a statistical software that allows you to enter your data to perform a wide range of statistical analyses on that data. It can be used to calculate many types of descriptive statistics including the ones discussed in the Descriptive Statistics article which can tell you a lot about your data in order to make more rational decisions. Descriptive statistics summaries in Minitab can be either quantitative or visual. Read more »»

Descriptive Statistics

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 »»

Value Stream Mapping


Value Stream Mapping

A Value Stream Map (VSM) is a visual representation that helps to understand the flow of value in a business process as perceived by the customer. Its primary goal is to identify and eliminate waste (Muda) and make the process as close to lean as possible. It is considered as an improvement tool rather than just a definition of how the process operates or should operate. Although it is often associated with manufacturing, it can also be applied in product development and service related industries such as: healthcare, hospitality and logistics.

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Scatter Plots

Scatter Plot

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.

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