Minimum Statistics Requirements for MSCA 602: Applied Linear Statistical Models
- Description summary measure from a sample: center and spread of distribution, quantiles.
- Data presentation: stem-and-leaf display, box-and-whisker plot, histograms and dot plots.
- Basic properties and rules: addition and multiplication rules; conditional probability; independence.
- Definition and properties of discrete and continuous random variables; the expected value (mean) and variance of a random variable.
- Normal distribution: properties of the normal distribution; standard normal variable.
- Measure of a sampling distribution; standard error.
- Normal approximation to sampling distributions (central limit theorem in the case of a sample mean).
- Statistical estimation
- The meanings of point and interval estimation. The cases of a single mean and the difference of two means from independent samples.
- The T distribution
- The F distribution.
- Hypothesis testing
- Hypothesis testing procedure;
- Type I and type II errors;
- The p-value of a test;
- Relations between tests and confidence intervals;
- Chi-square goodness-of-fit test for probability distributions.