## Statistics for Buiness Intelligence – Chi Square Tests

Chi square tests, namely chi-square goodness of fit test and chi-square test of independence, are used to analyse data that are a frequency distribution of discrete variables. Consider for example, a wine cellar that has four different categories of wine, a frequency distribution of the four varieties of wine can be analysed by such tests.Chi-Square … Read more

## statistics for business intelligence – ANOVA

Design of experiments : An experimental design is used to test a hypothesis by modifying one or more variables. The variables may be dependent or independent. Independent variables may be a treatment variable (can be modified) or classification variable (characteristic of the experimental factors, present prior to the experiment and is not modified during the … Read more

## statistics for Business intelligence – Inference for 2 populations

Here we consider comparing the statistic from two samples. we would compare the mean, population proportion and variance. The tests used would be the z test and the t- test. Some of the experiments would use independent samples. (members in both the samples are independent of each other)Difference in two means using z-statistic : according … Read more

## Statistics for Business Intelligence – Hypothesis testing

Hypothesis is defined in dictionary.com as ‘a proposition assumed as a premise in an argument’. This post explores the various kinds of hypothesis in statistics and methods to test them. Research hypothesis : A statement that is considered the outcome of an experiment or test, before the experiment is undertaken.Statistical hypothesis : This is used … Read more

## Statistics for Business Intelligence – Inferential Statistics 1

Inferential statistics is the term given to the branch of statistics that uses the information from the sample to infer the information about the population. For example, given a sample mean , the population mean (also called a parameter) can be determined using inferential statistics. Estimating population mean – Let us first look at estimating … Read more

## Statistics for Business Intelligence – Sampling

It is necessary to understand sampling techniques before data for a sample is gathered for analysis. Some of the terms that are important arePopulation – This is the complete set under consideration. For example a survey of food choices for a country might consider all citizens of the country.Frame – frame is the population where … Read more

## Statistics for Business Intelligence – Distribution

Discrete variables – Discrete variable take a set of values. for example, type of card drawn from a pack of cards can take any of the four values: hearts, spades, clubs or diamonds.Continuous values – These can take any values within a specified range. For example height of students in a class can take any … Read more

## Statistics for Business Intelligence – Shape

In this post i will discuss the measures of shape used for statistical analysis, specifically skewness and kurtosis. I will also discuss the box and whisker plot. Skewness – A normal distribution is a bell curve that is perfectly symmetric. perfect symmetry implies that the values are distributed equally around the center. a graph is … Read more

## Statistics for Business Intelligence – Descriptive Statistics

In this post we look at descriptive statistics as a means for data exploration. Descriptive analysis refers to a group of methods that gives summary information about the data. For example consider the sales figures for a retail clothes outlet. An important figure would be the average of sales for a particular day of the … Read more

## Statistics for Business Intelligence – Introduction

An understanding of Statistics is imperative before delving into the tools and methods of business intelligence and analysis. We will spend some time on understanding the basics of Statistics for data analysis and in subsequent posts try to give more detailed explanation of the various methods involved.Statistics for data analysis can be broadly divided into … Read more