CFA® Level 1 Quantitative Methods (2024) - Part 1

Learn to classify data as numerical (continuous or discrete) or categorical (nominal or ordinal); study time series, cross-sectional, and panel data, plus structured and unstructured data, with frequency distributions.

Explore histograms, frequency polygons, cumulative distribution charts, bar charts, tree maps, word clouds, line and bubble line charts, scatterplots, scatterplot matrices, and heatmaps, with guidance on when to use each.

Choose visualization types to compare categories, time trends, and distributions. Master measures—mean, median, mode, trimmed and winterized means, weighted, geometric, and harmonic means—and quartiles, quintiles, and percentiles with box-and-whisker plots.

Explore measures of dispersion, including range, mean absolute deviation, and variance. Calculate standard deviation, target downside deviation, coefficient of variation, and examine covariance, correlation, and scatter plots.

Define random variable, outcome, and event; distinguish mutually exclusive and exhaustive events. Apply probability rules, including multiplication, addition, and total probability, using conditional and unconditional cases, odds, and expected value.

Compute the variance from probabilities and inflows, using the expected value 34 and standard deviation 17.44, and apply covariance, correlation, and 30%/70% portfolio weights to assess portfolio variance.

Apply Bayes theorem to update rain probabilities after new information, using a tree diagram and joint probabilities, then master counting principles—multiplication rule, factorial, labeling, combinations, and permutations—with calculator steps.

Define probability distributions and distinguish discrete from continuous random variables, then explore uniform and continuous uniform distributions, cumulative distribution functions, and binomial concepts including Bernoulli trials, expected value, and variance.

Explore the normal distribution and its symmetry around the mean, memorize 68–95–99% rules, distinguish univariate from multivariate distributions, and use the standard normal z table to construct confidence intervals.

Explains the safety first ratio for minimizing downside risk and introduces lognormal and normal distributions, continuously compounded returns, the t and chi-square distributions, plus Monte Carlo simulation.

Understand population and sample relations, parameters, and sample statistics. Review probability sampling (simple random, systematic, stratified, cluster) and non-probability methods (convenience, judgment), plus sampling error and the central limit theorem.

Estimate the population mean with confidence intervals using z or t statistics, and compare bootstrap and jackknife resampling while noting data-snooping and survivorship biases.

Understand hypothesis testing basics: null vs alternative, one-tailed and two-tailed tests, alpha, critical values, test statistic, p-value, type I/II errors, power, and economic significance versus statistical significance.

Explore the full CFA® Level 1 quantitative methods curriculum beyond this crash course, covering economics, financial statement analysis, and fixed income, with resources at Wall Street notes dot com.