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Statistics is used to gather information from samples of data to make inferences about the overall population. However, as our computational abilities increase, we can process and analyze more and more data--potentially the entire data sets of all trading activity.

Why, then, is statistics still relevant to modern quantitative finance?

**A.** Sampling algorithms run faster than looking at the entire data set.

**B.** Statistics can help determine the significance of results/models.

**C.** Statistics can help avoid overfitting.

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One of the uses of statistics in quantitative finance, as mentioned in the previous question, is to determine the significance of certain results. A classic benchmark for statistical significance is a **p-value** of 5%.

**True or False?**

Achieving a \(p\)-value of 5% means that there is a 5% chance that the original hypothesis is true.

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