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There are a variety of methods of regression analysis, each with its own strengths and weaknesses. The most commonly used methods are linear regression, logistic regression, and Poisson regression.
Linear regression is used when the data is assumed to be linear in nature. Logistic regression is used when the data is assumed to be binary (e.g., success/failure, yes/no), while Poisson regression is used when the data follows a Poisson distribution, and is used for modeling count data.
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