Master of Science in Management (MSc)

Description Statistics

• 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.

Probability

• Basic properties and rules: addition and multiplication rules; conditional probability; independence.

Random Variables

• 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.

Sampling Distribution

• Measure of a sampling distribution; standard error.
• Normal approximation to sampling distributions (central limit theorem in the case of a sample mean).

Statistical Inference

• 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.