## Design of Experiments – Introduction

Experiments are performed in various fields to understand the behaviour of a system. In this post we will analyse the common terms used during an experiment design. Experiment : An experiment can be defined as a test or a group of test wherein changes are made to the input variables and the effect of that … Read more

## Dimensional Modeling

A company that has a huge volume of data builds a data warehouse so that it can generate reports, perform analytics and make informed decisions. The process of building a data warehouse from a transactional or source system is important and the process that a company selects depends on its long term vision and goal … Read more

## Introduction to data Warehouse

Many companies spend a fortune in organizing and storing their data. The amount of data that is generated daily may vary for different companies but it is not uncommon to hear of scores of GB of data for medium sized companies and terabytes of data for large enterprises. It is indeed challenging to store this … Read more

## Statistics – Examples

T-Test:Problem : A swimming instructor wants to prove that the swimming speed of an athlete increases if the athelete performs some specific exercises before the swim. He undertakes an experiment with 16 participants and randomly assignes 8 participants to each team. For team A he recommends some common exercises and for team B he recommends … Read more

## Use of Statistics – Practical Considerations

It is often confusing to decide on which statistic to use at what point. Also researchers need to be careful that the statistics they present does truly apply in the context of the problem. Statictics can be misleading and probably incorrect if used outside the boundaries set by its assumptions. In this post we analyse … Read more

## Non Parametric Statistics

The earlier posts on inferential statistics show methods that work on data whose population parameters and distribution are known. However, there are cases where the population parameters are not known. In such cases, no assumption can be made about the population statistics and hence parametric methods cannot be used. In such cases there are certain … Read more

## Multiple Regression model building

Polynomial Regression: First order regression models contain predictors that are single powered. Polynomial models have one or more predictors having a power of more than one. A quadratic model has a predictor in the first and second order form.Since the constants are linear, the variable x1 squared can be recoded to x2 and then the … Read more

## T-Test, F-Test and P-value

Two very important tests in statistical analysis are the t-test and the f-test. However, some confusion may arise for a new user as to the difference between the two tests. In this post I will try and present the difference between the two tests and when each should be used. But before we understand the … Read more

## Statistics for Business Intelligence – Multiple Regression

Simple regression deals with predicting a dependent variable using an independent variable using a linear regression equation. In multiple regression analysis there are more than one independent variables or at least one non linear independent variable. Multiple Regression Model :The multiple regression model is of the form.where y = the value of the dependent variable.beta0 … Read more

## Statistics for Business Intelligence – Simple Regression

Introduction: In many situations, a relationship between two variables needs to be analysed. For example, a car manufacturer would like to know whether the number of cars bought in the city is related to the average household income in the city, or a sales manager would like to know if the sales revenue is dependent … Read more