## How are normal distribution and t distribution implemented in statistics? How do Data Scientists use these in real life?

The normal distribution and t-distribution are two of the most commonly used probability distributions in statistics. They are used to model the distribution of continuous variables, such as heights, weights, and test scores, and are essential tools for data scientists in analyzing and interpreting data. The Normal Distribution: The normal distribution is a continuous probability […]

## How do Data Scientists use Black-Scholes model on ClickHouse?

The Black-Scholes model is a mathematical formula used to estimate the price of European-style options, which are financial contracts that give the holder the right, but not the obligation, to buy or sell an underlying asset at a predetermined price within a specified time period. The formula was developed by Fischer Black and Myron Scholes […]

## Data Scientists Education Series – What is Chebyshev’s InEquality in Statistics? How do Data Scientists use Chebyshev’s InEquality? How to implement Chebyshev’s InEquality in ClickHouse?

Chebyshev’s inequality is a statistical theorem that provides a bound on the probability that a random variable deviates from its mean by more than a certain number of standard deviations. Specifically, it states that for any random variable X with finite mean μ and finite variance σ^2, the probability that X deviates from its mean […]

## Data Scientist Education Series – How do Data Scientists use Skewed Q-Q plots in real life?

Skewed Q-Q plots are a useful visualization tool for data scientists when they are dealing with non-normal distributions. In real life, data scientists use skewed Q-Q plots to perform the following tasks: Overall, skewed Q-Q plots are a powerful tool for data scientists when dealing with non-normal distributions. They provide insights into the distribution, skewness, […]