Here are the essential concepts you must grasp in order to answer the question correctly.
P-Value
The P-value is a statistical measure that helps determine the significance of results in hypothesis testing. It represents the probability of obtaining a test statistic at least as extreme as the one observed, assuming the null hypothesis is true. A smaller P-value indicates stronger evidence against the null hypothesis.
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Hypothesis Testing
Hypothesis testing is a statistical method used to make decisions about a population based on sample data. It involves formulating a null hypothesis (H0) and an alternative hypothesis (H1), then using sample data to determine whether to reject H0. The outcome is often influenced by the chosen significance level (alpha).
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Significance Level (Alpha)
The significance level, denoted as alpha (α), is the threshold for deciding whether to reject the null hypothesis. Commonly set at 0.05, it represents a 5% risk of concluding that a difference exists when there is none. If the P-value is less than alpha, the null hypothesis is rejected, indicating statistically significant results.
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Step 4: State Conclusion Example 4