Statistics
5 articles ~22 min
- Confidence Intervals A confidence interval gives a range, not just a point estimate, that likely contains the true parameter. Understanding what '95% confidence' actually means is essential for interpreting quant research.
- Descriptive Statistics: Mean, Median, Mode Before making inferences, you first describe what you see. Mean, median, mode, variance, and standard deviation are the vocabulary of data summarization.
- Hypothesis Testing: P-Values and Significance Hypothesis testing is how you distinguish real patterns from noise. The p-value tells you how surprised you should be by data, if a null hypothesis were true.
- Regression Analysis Basics Regression finds the best-fitting line through a cloud of data points. Understanding simple linear regression is the foundation for all factor models and predictive modeling in quant finance.
- Time Series: Stationarity and Autocorrelation Asset prices are not independent over time; today's return is related to yesterday's. Understanding stationarity and autocorrelation is essential before doing any time series analysis.