Hypotheses
In data science, hypotheses refer to proposed explanations or predictions about a phenomenon or relationship between variables. Hypotheses are formulated based on available data and prior knowledge, and are tested using statistical methods to determine their validity. The process of hypothesis testing involves defining a null hypothesis, which assumes that there is no significant difference or relationship between variables, and an alternative hypothesis, which proposes that there is a significant difference or relationship. The data is then analyzed to determine the probability of obtaining the observed results if the null hypothesis were true. If the probability is low enough (typically less than 5%), the null hypothesis is rejected in favor of the alternative hypothesis, indicating that there is evidence to support the proposed explanation or prediction.
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