More feature flags related terms



Correlation is a statistical measure that expresses the extent to which two variables change together. If the value of one variable increases and the other variable tends to also increase, there is a positive correlation. Conversely, if an increase in one variable tends to be associated with a decrease in the other, this is a negative correlation. Correlation coefficients are used to quantify the degree of correlation between variables.


The most common measure of correlation in statistics is the Pearson correlation coefficient, denoted as r. It ranges from -1 to +1, where +1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no linear correl

\[ r = \frac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum (x_i - \bar{x})^2} {\sum (y_i - \bar{y})^2}} \]

where x_i and y_i are the individual sample points indexed with i, bar{x} is the mean of the x values, and bar{y}is the mean of the y values.


Understanding the correlation between different variables can help in predicting one variable based on the known value of another. In business, for example, understanding the correlation between advertisement spend and sales can help in budget allocation. In product development, understanding the correlation between features and user satisfaction can guide feature prioritization.



Correlation is a powerful statistical tool that provides insights into the relationship between variables, enabling better data-driven decisions. However, it's important to remember its limitations and ensure that it's used appropriately, taking into consideration the broader context of the data and the specific questions being asked.

Conversion rate

Conversion rate is the percentage of website visitors who complete a desired action, such as making a purchase, indicating the effectiveness of marketing and website design efforts in driving revenue.

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CUPED is a technique that uses pre-experiment data to reduce variance in A/B testing, improving result sensitivity and reliability by focusing on the true effects of the experimental changes.

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Customer journey management

Customer journey management optimizes the entire customer experience from awareness to post-purchase, focusing on cohesive interactions across touchpoints to enhance satisfaction, loyalty, and conversions.

Learn about Customer journey management

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