Discuss the importance of assumptions in hypothesis testing. What are some common assumptions that must be met for the results to be valid?
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Assumptions in hypothesis testing are crucial because they ensure the validity and reliability of the results. Violating these assumptions can lead to incorrect conclusions. Common assumptions include:
1. Independence: Observations must be independent of each other.
2. Normality: Data should follow a normal distribution (important for parametric tests).
3. Homogeneity of Variance: Variances across groups should be equal.
4. Random Sampling: Samples must be randomly selected to generalize results.
5. Scale of Measurement: Data must meet the scale requirements of the chosen test (e.g., interval or ratio scale).
Ensuring these assumptions are met helps maintain the integrity of statis
tical inferences.