Linear Regression Analysis

Linear Regression Analysis

The term multiple regression (linear regression analysis with more than one variable) was first used by Pearson in 1908. Multiple regression is a statistical technique that help us in understanding about the relationship between several independent or predictor variables and a dependent variable (also called criterion variable). Let us take an example to understand this in some detail. Suppose that you are a researcher and you record data of 1000 MBA […]

Comparing CHAID, CARD, and QUEST Algorithms for Building Decision Trees

Comparing CHAID, CARD, and QUEST Algorithms for Building Decision Trees

Decision tree is a popular machine learning technique that is used to solve classification and regression problems.  The three most popular algorithm choices that are available when you are running a decision tree are QUEST, CHAID, and CART. When you are working on a classification problem (dealing with categorical dependent variable), any of the three algorithms can be used. Though QUEST algorithm is generally faster compared to the other two […]

Cronbach’s Alpha

Cronbach’s Alpha

Cronbach’s alpha measures the internal consistency of a set of items. In other words, it measures how closeness of a set of items within a group. It is considered as a measure of scale reliability. If you want to test the unidimensionality of a measure, a ‘high’ value of cronbach’s alpha is not sufficient. In order to provide strong evidence that the scale or measure that we are testing is […]

Data Analysis Chapter of Your Research Work

Data Analysis Chapter of Your Research Work

Research Data Analysis: Significant Part of Your Research I am sure that as a researcher you will not deny the fact that your dissertation or thesis is the single most important document that you’ll ever create and it offers you a good placement opportunity, scope of good publication, and also widens your knowledge about your research area. However, writing a dissertation or thesis is not as straightforward as it seems […]

What is Stationarity in Time Series Analysis?

What is Stationarity in Time Series Analysis?

Stationarity in Time Series is one of the common assumptions in many of the time series analysis techniques. A stationary time series (or the underlying process) has mean, variance, and autocorrelation structure that do no change over time. Visually, a stationary time series will be a flat looking series, without trend, constant variance over time, a constant autocorrelation structure over time and no periodic fluctuations. In real-life scenarios lot of […]