Talking about our everyday take away from the class, there may be certain things that you tend to miss out on. Well, if you have missed the presentation which one of my group members had given, here it is.

The main objective of this analysis is to infer the relationship between the randomness levels in behavior of the phone users in a cellular network. While individual phone user’s calling behavior is random, some users might be more predictable than others. Being more predictable can also mean being less random. To quantify the randomness or amount of predictable structure in an individual calling pattern, the information entropy can be used. The information entropy or Shannon’s entropy is a measure of uncertainty of a random variable.

The calling pattern is understood from the Calling Time, Interconnected Time, Talk time & Location of the call. These calling patterns and the factors affecting them are studied using correlation coefficient and factor analysis.

If a factor has a low Eigen value, then it is contributing little to the explanation of variances in the variables and may be ignored as redundant with more important factors. If a factor has Eigen Value of more than 1, then it is considered as effective component and is not redundant. Scree Plot helps in selecting the number of factors to be retained in order to account for most of the variation. The Scree Plot denotes the relationship between the factors of variance. It helps you determine which factors to retain.

- What we understood from the analysis is that User’s randomness level based on location has high correlation to the randomness level in time of making phone calls and vice-versa.
- Randomness level based on user’s inter-connected time has a high correlation to the randomness level in time spent talking on each phone call

**Author**: Mohamed Sahle

**Group**: Marketing 5

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