A quant sees a sample of returns rather than the full process that produces them. Statistics describes that sample and measures uncertainty about what lies beyond it. This lesson estimates means and covariance, then fits a simple line between market and fund returns. A good fit is a starting point for research, not proof of a causal effect or a profitable strategy.
Learning objectives. By the end of this note you should be able to:
- distinguish a population parameter from a sample statistic;
- compute sample mean, median, variance, standard deviation and standard error;
- interpret a scatterplot, sample covariance and correlation;
- fit a simple least-squares line from summary quantities;
- calculate residuals and state what regression does not establish.
In this lesson
- Population, sample and summaries
- Two variables: association before regression
- The simple fitted line
- What regression does not prove
- A residual is a vertical difference
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