Null Hypothesis
In data science, the null hypothesis is a statement that assumes there is no significant difference between two or more sets of data. It is often used in hypothesis testing to determine whether a certain observed phenomenon is due to chance or a real effect. The null hypothesis is typically the opposite of the alternative hypothesis, which is the hypothesis that there is a significant difference between the sets of data being compared. In order to test the null hypothesis, statistical methods are used to calculate the probability of obtaining the observed results by chance. If this probability is below a certain threshold, typically 5%, the null hypothesis is rejected and the alternative hypothesis is accepted. If the probability is above the threshold, the null hypothesis is not rejected and it is assumed that the observed phenomenon is due to chance.
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