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NSWMaths AdvancedQuick questions

Year 12: Statistical Analysis

Quick questions on Continuous random variables: probability density functions, cumulative distributions, mean and variance

6short Q&A pairs drawn directly from our worked dot-point answer. For full context and worked exam questions, read the parent dot-point page.

What are probability density functions?
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A continuous random variable XX is described by a probability density function ff satisfying
What are probabilities as integrals?
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For any interval [c,d][c, d] inside the support, the probability is the area under the density over that interval:
What is cumulative distribution function?
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The cumulative distribution function (cdf) accumulates probability from the left:
What is mean, variance, median, mode?
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The mean (expected value) weights each value xx by its density and integrates:
What are the standard problem types?
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NESA questions on this dot point fall into a small number of recognisable shapes, and naming the type tells you the first move:
What is sketching the density?
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A quick sketch of ff over its support guides the work. The total area under the curve must be 11, the median splits that area in half, and the mode sits under the highest point of the curve. For a symmetric density the mean, median and mode coincide at the centre of symmetry, which can save an integral if you spot the symmetry early.

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