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Learning goals
- Interpret point estimates, confidence intervals, and hypothesis tests clearly for an audience without statistical training.
- Construct common estimators, statistical tests and confidence interval procedures using probability theory.
- Evaluate the relative strengths and limitations of several estimation or inference procedures for the same problem using mathematical concepts including unbiasedness, efficiency, and power.
- Recommend an approach and carry out estimation and inference for canonical statistics problems including tests of association between two variables and fitting probability distributions to univariate data.
Prerequisites
- STAT 134 or an equivalent course in probability theory.
- Multivariable calculus, especially Lagrange multipliers.
- Familiarity with moment-generating functions.
- Familiarity with linear algebra (matrix operations, inverses, and eigenvalues) for chapter 14.
- Familiarity with basic R concepts equivalent to the first ~6 weeks of Stat 133. Unless otherwise noted assignments involving computing must be completed in R.