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Linear regression is a kind of statistical analysis that attempts to show a relationship between two variables. Linear regression looks at various data points and plots a trend line. Linear regression can create a predictive model on apparently random data, showing trends in data, such as in cancer diagnoses or in stock prices.
Linear regression is an important tool in analytics. The technique uses statistical calculations to plot a trend line in a set of data points. The trend line could be anything from the number of people diagnosed with skin cancer to the financial performance of a company. Linear regression shows a relationship between an independent variable and a dependent variable being studied.
There are a number of ways to calculate linear regression. One of the most common is the ordinary least-squares method, which estimates unknown variables in the data, which visually turns into the sum of the vertical distances between the data points and the trend line.
The calculations to perform linear regressions can be quite complex. Fortunately, linear regression models are included in most major calculations packages, such as Excel, R, MATLAB and Mathematica.