Six Sigma and Statistics

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Project Charter: What is a six sigma project charter and how to create it in 7 steps[Free download]

What is project charter in six sigma

Project charter in six sigma very important requirement for the project. It is a living document for the project and it lays out every important project variable. The creation of a project charter is one of the first steps in six sigma project. It is a part of the Define phase of DMAIC process. This includes everything from who is participating in the project, to the project goals. Let us take few minutes to understand the different components of project charter step by step.

Step-1: Defining the project name

The very step in making a Project Charter is to name the project. The project name should reflect what the project is looking … Continue Reading

descriptive statistics

What is Descriptive Statistics: How to calculate it in excel using the Data Analysis Tool Pack

What is descriptive statistics

Descriptive statistics are used to describe, show or summaries the basic features of a data set in a meaningful way. It provides basic summaries of the data like mean, median etc. It is very useful as if we only present data it wouldn’t make any meaning but while using descriptive analysis the same data can be presented in a very meaningful way.

How to use Descriptive Statistics in Excel

To use Descriptive Statistics in Excel we will use Data Analysis tool pack. First we will go in Data tab Data Analysis. After clicking Data Analysis a new box will come like below image.

What is Descriptive Statistics
What is Descriptive Statistics

This tool box contains different options like Descriptive … Continue Reading

Difference between Normalization and Standardization: 2 ways of feature scaling your data, How to do it in Excel

Difference between Normalization and Standardization

Normalization and Standardization are very integral parts of data processing. While processing data we often encounter different kind of variables which have different original scale. Using these scale can put more weightage to variables which have a large range in their data. In order to deal with this problem, we will be using feature rescaling of the independent variables so that the weights of all variables will be on the same scale.

In this article we will be discussing about the two feature scaling methods i.e. Normalization and Standardization. Both the terms are sometime used interchangeably. But they usually refer different things.


It is also known as Z-score normalization and in it features … Continue Reading

type of variables

Statistical Testing: How to select the best test for your data? || Hypothesis Testing

Statistical Testing

The most confusing aspect of statistical testing is which test needs to use and when, especially those who are new to statistical analysis. Through this post I will try to make it easy to understand in choose the correct statistical test for our data.

Let us first understand the variables.

  • Dependent variable– also know as output variable
  • Independent variables – also known as a predictor variable which impact value of the dependent varaible

Type of variables

Statistical Testing
Type of Variables

Why do we need statistical tests

Statistical testing is required to find out risks associated with decision-making, which comes from a hypothesis or a gut feeling or assumption. There are two kindly of risk which is associated with … Continue Reading

Difference between type 1 and type 2 errors in statistical hypothesis testing: How to interpret it

Difference between type 1 and type 2 errors

In statistical test theory, the concept of a statistical error is an integral part of hypothesis testing. The Hypothesis test is about choosing between the two hypotheses, the Null Hypothesis or Alternative Hypothesis. The Null hypothesis is presumed to be true until the data provide convincing evidence against it.

What is Hypothesis Testing and How to do Hypothesis testing

Any hypothesis testing is not 100% accurate. There will be scope for some error. There are two types of error that can occur. These errors are :

  • Type 1 and
  • Type 2.
Difference between type I and type II errors
Type I and type II errors in statistical hypothesis testing

In the above image we can see there are four different … Continue Reading

What is a scatter plot: How to read it and method to create it in excel

What is a scatter plot?

Scatter plots also known as scatter charts and scatter diagrams used to show relationships between two variables and the relationship between two variables is called their correlation. It’s a 2-D plot and it plots data points on a horizontal and a vertical axis to show how much one variable is affected by another. In the scatter plot, all data points are represented by dots in the plot.

If the points are close to making a straight line in the plot then it is considered as highly correlated variables. While if they are equally distributed all over the plot then their correlation is weak or zero.

When to use scatter diagram

When we have a … Continue Reading

Understanding and interpreting boxplots: How to create them in Excel

Understanding and interpreting boxplots

What is boxplot

Boxplot also known as box and whisker plot is used in explanatory data analysis. It is used to show the variance and central tendency of any data set. By this, we can visually represent the distribution of data in a dataset. It also helps in comparing two or more sets of data.

How box plots look like

Box plot is a standardized way of showing distribution of data on the basis of five number summary.

Understanding and interpreting boxplots
Box plot structure

PS: Above image is taken from

In the above image, we can see the five summaries as the minimum(min), Q1(lower quartile), median(Q2), Q3(upper quartile), and maximum(max). We also see min and Q1 are connected … Continue Reading

How to create a Pareto Chart in Excel – 80/20 Rule or Pareto Principle

How to create a Pareto Chart in Excel

Pareto Chart is the presentation of Pareto principles also known as 80/20 rules, the law of the vital few, or the principle of factor sparsity is used in statistics and quality control. This principle explains 80% of the consequences come from 20% of the causes( the vital few). This 80/20 proportion can be changed in practical life based on the actual requirement. Examples of the Pareto principle is given below:

  • 80% money earned by 20% of people.
  • top 20% reported bug causes 80% system crash
  • 20% of drivers cause 80% of all traffic accidents.
  • 80% of the pollution originates from 20% of all factories.
  • 20% products of a company generate 80% revenue.
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What is Histogram : How to create it in excel by 2 different ways

What is Histogram

Histogram is a chart that helps us discover and present continuous data basis frequency distribution. It is sort of bar chart just the major difference is that histogram used to show frequency of data in the data set which has been divided in classes also known as bin.

Histogram also helps us to find underlying distribution of data, outliers, skewness and kurtosis. It helps us to check how the output of a process looks like, is process able to meet customers requirement and many more other thing.

How to create Histogram in excel

I will explain 2 methods of creating Histogram in excel

  1. by creating frequency table
  2. by excel inbuilt histogram chart

By creating frequency table:

We … Continue Reading

What is Hypothesis testing in statistics: How to do Hypothesis testing,5 steps process

What is Hypothesis testing in statistics

Hypothesis testing in statistics is a process by which we are confirming our hypothesis or prediction statistically. Scientists mainly use it to test the specific prediction from some theory or hypothesis or even from gut feelings.

Examples of Hypothesis Testing:

  1. The ability of Vitamin C to cure or prevent cold,
  2. Children of obese parents are more likely to be obese
  3. Men have taller than women
  4. Tenure calling operators have less handling time than a new operator.

Type of Hypothesis testing :

  1. Null Hypothesis : Null hypothesis states that there is no difference in parameters for two or more populations. If any observed difference in a sample is due to chance or sampling-related error, it
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