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Quick glossary: Statistics

Originally Published:
Jun 2016

Successful competitive analysis relies on the collection of data--lots of data. To turn that data into useful information, enterprises use statistical analysis. Here’s a short list of terms you’ll need to know to understand the results.

From the glossary:

For most modern enterprises, successful competitive analysis and business intelligence depends on collecting and analyzing a lot of data. To turn that data into useful and actionable information for decision makers, enterprises often use some form of statistical analysis.

The transformation of data into information is generally performed by people trained in the science of statistics, probabilities, and analysis. However, that does not excuse decision makers from learning a few key terms, if for no other reason than to better comprehend the analysis as it is being presented. This list of 22 terms and concepts will help you get a general handle on statistics even if you have never been trained in the actual science.

Bayesian statistics An analytic technique in which assumptions about a variable are revised in the light of new data by using a weighted average of the previous assumption about a variable.

Correlation An expression of the degree and type of relationship between two or more variables as they vary together over a specific period of time. Correlation can be positive or negative and is generally expressed in a range from +1 to -1.

Data mining An analysis technique used to sift through large amounts of data for useful information. The sifting is often performed by algorithms that attempt to reveal hidden trends, patterns, and relationships in the data.

Differential analysis A decision-making technique in which the evaluation of possible alternatives is confined to differing or unique factors. For example, if two widgets are physically identical but one is guaranteed for life, that differentiating factor would be in its favor during the decision-making process.

Exponential growth A result in which the number or size of some measureable data grows at an ever-increasing rate, such as compound interest.

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