Cluster analysis groups individuals or objects into clusters objects in the same cluster are more similar to one another than they are to objects in other clusters. The attempt is to maximize the homogeneity of objects within the clusters while also maximizing the heterogeneity between the clusters. Like factor analysis, cluster analysis is also an inter-dependence technique.

**A Simple Example**

Suppose, you have done a pilot marketing of a candy on a randomly selected sample of consumers. Each of the consumers was given a candy and was asked whether they liked it and whether they will buy it. …

Suppose, we are interested in consumers evaluation of a brand of coffee. We take a random sample of consumers whom were given a cup of coffee. They were not told which brand of coffee they were given. After they had drunk the coffee, they were asked to rate it on 14 semantic — differential scales. The 14 at-tributes which were investigated are shown below:

1. Pleasant Flavor — Unpleasant Flavor

2. Stagnant, muggy taste — Sparkling, Refreshing Taste

3. Mellow taste — Bitter taste

4. Cheap taste — Expensive taste

5. Comforting, harmonious — Irritating, discordant

6. Smooth, friendly taste…

A time series is a sequence of data points, measured typically at successive times, spaced at uniform time intervals. Now the period or the uniform time interval can be as large as a century if you collect geological data, can be as small as a second if you collect biological data, and can be a quarter if you consider economic data. The important issue is that the time interval must be uniform.

Time series analysis comprises methods for analyzing time series data in order to ex-tract meaningful statistics and other characteristics of the data.

Time series forecasting is the use…

**Necessity of antenna miniaturization in wireless communication**

In almost all areas of electrical engineering the research interest has been shifted toward miniaturization. Electromagnetism and antennas in particular, are no exception. With the rapid development in wireless systems all over the world, miniaturized antennas have become an active area of research for many antenna engineers. In past several years, a large emphasis has been placed towards miniaturized antenna design. There are many reasons for using small antennas, most of which are physical constraints. For example, high speed aircraft or warships are easy to be damaged due to mechanical strength i.e. wind…

In a nutshell, logistic regression is multiple regression but with an outcome variable that is a categorical dichotomy and predictor variables that continuous or categorical. In plain English, this simply means that we can predict which of two categories a person is likely to belong to given certain other information.

**Example: Will the Customer Leave the Network?**

This example is related to the Telecom Industry. The market is saturated. So acquiring new customers is a tough job. A study for the European market shows that acquiring a new customer is five time costlier than retaining an existing customer. In such…

In regression analysis we fit a predictive model to our data and use that model to predict values of the dependent variable from one or more independent variables.

Simple regression seeks to predict an outcome variable from a single predictor variable whereas multiple regression seeks to predict an outcome from several predictors. We can predict any data using the following general equation:

(Outcome)i = (Model)i + (Error)i

The model that we fit here is a linear model. Linear model just means a model based on a straight line. …

**STEPAR (Stepwise Auto-regression)**

Here we fit a time trend model to the series and takes the difference between each value and the estimated trend. This process is called DETRENDING. Then, the remaining variation is fit using an autoregressive model. We will learn about the Autoregressive Model in the coming segments.

**EXPONENTIAL**

Exponential smoothing forecasts are forecasts for an integrated moving-average process; however, the weighting parameter is specified by the user rather than estimated from the data. …

Data