Regression models are widely used as statistical technique for prediction the outcome based on observed data.

Linear regressions allows describe how dependent variable (outcome) changes relatively to independent variable(s) (feature, predictor).

When there is one independent variable and one dependent, it is called simple linear regression (SLR).
When there is more than one independent variable and one dependent, it is called multiple linear regression (MLR).

A simple linear regression equation looks like:

y = a + bx

where:
x — the independent (explanatory) variable,
y — the dependent (responce) variable,
a — intercept,
b — slope of the line (coefficient).


Data science is an interdisciplinary field which focuses on making inferences from large data sets. This field includes data cleaning, manipulation, analysis, visualization and presentation of findings in order to inform a high-level decisions in an organization. As such, it incorporates skills from computer science, mathematics, statistics, information visualization, graphic design, and business.

Big data quickly become a vital tool for business everywhere from Amazon’s sales to TV and drug discovery. Data scientists are responsible for breaking down big data into usable information that guides decision making. The impact of big data in our days can not be over estimated…

Vadym Byesyedin

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