The null hypothesis is a statement that assumes there is no significant difference or relationship between variables in a statistical analysis.
Imagine you are accused of cheating on a test. The null hypothesis would be that you did not cheat, and any evidence against this hypothesis would suggest otherwise.
Alternative Hypothesis (Ha): The alternative hypothesis is the opposite of the null hypothesis and suggests that there is a significant difference or relationship between variables.
Type I Error: Type I error occurs when we reject the null hypothesis when it is actually true, indicating a false positive result.
Significance Level: The significance level, denoted by alpha (ɑ), determines how much evidence we need to reject the null hypothesis. It represents the probability of making a Type I error.
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