# 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.

# Normality Testing in Minitab

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

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 »

# Descriptive Statistics in Minitab

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 »

# Scatter Diagram

Many situations require the investigating whether a relationship exists between two or more variables. A line manager, for example, may want to check the relationship between the number of training hours and employee productivity, or if the number of defects is a function of the experience of the person causing it. A call center manager may be interested in studying the relationship between the number of people working on a shift and the average answer time.