Hypothesis testing (CFA Level I Suggested Reading)
The null hypothesis and alternative hypothesis and one-tailed and two-tailed hypothesis tests
A significance level and how significance levels are used in hypothesis testing
A Type I and a Type II error
The power of a test
The decision rule
The relationship between confidence intervals and tests of significance
The difference between a statistical decision and an economic decision
The p-value approach to hypothesis testing
The test statistic and the results for a hypothesis test about the population mean of a normal distribution with (1) known or (2) unknown variance
The use of the z-test in relation to the central limit theorem
The test statistic and the results for a hypothesis test about the equality of two population means of two normally distributed populations based on independent samples
The mean difference for two normal distributions (paired comparisons test)
The difference between parametric and nonparametric tests
Correlation and regression (CFA Level II Suggested Reading)
A scatter plot
The covariance between two random variables
A correlation coefficient
How correlation analysis is used to measure the strength of a relationship between variables
A test of the hypothesis that the population correlation coefficient equals zero and whether the hypothesis is rejected at a given level of significance
An outlier and how outliers can affect correlations
The nature of a spurious correlation
Dependent and independent variables in a linear regression and the slope and the intercept terms in a regression equation
Linear regression, the standard error of the estimate and the coefficient of determination
A confidence interval for a regression coefficient
The test statistic and hypothesis test about the population value of a regression coefficient
A regression coefficient
A predicted value for the dependent variable, given an estimated regression model and a value for the independent variable and a confidence interval for the predicted value of a dependent variable
The use of analysis of variance (ANOVA) in regression analysis and an F-statistic
The limitations of regression analysis
Multiple regression (CFA Level II Suggested Reading)
How to formulate a multiple regression model where the independent variables are continuous or discrete
How to calculate predicted values, given a regression model and values for the independent variables Calculate measures of the significance of the model overall, and of individual coefficients
The assumptions that go into deriving a regression model
Determine confidence levels for predicted values
Sources of error in regression models
Time series analysis (CFA Level III Suggested Reading)
Time series models, including linear, log-linear, autoregressive (AR), moving average (MA), and autoregressive moving average (ARMA)
Limitations of these models
Corrective measures for the problems, such as unit roots
Portfolio analysis (CFA Level III Suggested Reading)
Math required for portfolio management
Modern portfolio theory (MPT)
Capital asset pricing model (CAPM)
Arbitrage pricing theory (APT)
Multifactor models
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