## 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

## 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