Data Analytics Made Accessible by Anil Maheshwari

Author:Anil Maheshwari
Language: eng
Format: mobi, pdf
Published: 2014-04-30T14:00:00+00:00

Q1: What is the impact of this story on traditional pollsters & commentators?

Correlations and Relationships

Statistical relationships are about which elements of data hang together, and which ones hang separately. It is about categorizing variables that have a relationship with one another, and categorizing variables that are distinct and unrelated to other variables. It is about describing significant positive relationships, and significant negative differences.

The first and foremost measure of the strength of a relationship is co-relation (or correlation). The strength of a correlation is a quantitative measure that is measured in a normalized range between 0 (zero) and 1. A correlation of 1 indicates a perfect relationship, where the two variables are in perfect sync. A correlation of 0 indicates that there is no relationship between the variables.

The relationship can be positive, or it can be an inverse relationship. i.e. the variables may move together in the same direction or in the opposite direction. Therefore, a good measure of correlation is the correlation coefficient, which is the square root of correlation. This coefficient, called R, can thus range from -1 to +1. An R value of 0, signifies no relationship. An R value of 1 shows perfect relationship in the same direction, and an R value of -1 shows a perfect relationship but moving in opposite directions.

Given two numeric variables X & Y, the co-efficient of correlation R is mathematically computed by the following equation. X-bar is the mean of x, and y-bar is the mean of y.

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