Statistics for Business and Economics

In today’s economic environment it is practically impossible to avoid dealing with data gathering and analysis. This textbook provides a comprehensive overview of the main topics in the area of statistic analysis for business and economics.

This compendium aims at providing a comprehensive overview of the main topics that appear in any well-structured course sequence in statistics for business and economics at the undergraduate and MBA levels. The idea is to supplement either formal or informal statistic textbooks such as, e.g., “Basic Statistical Ideas for Managers” by D.K. Hildebrand and R.L. Ott and “The Practice of Business Statistics: Using Data for Decisions” by D.S. Moore, G.P. McCabe, W.M. Duckworth and S.L. Sclove, with a summary of theory as well as with a couple of extra examples. In what follows, we set the road map for this compendium by describing the main steps of statistical analysis.

1. Introduction
1.1 Gathering data
1.2 Data handling
1.3 Probability and statistical inference

2. Data description
2.1 Data distribution
2.2 Typical values
2.3 Measures of dispersion

3. Basic principles of probability
3.1 Set theory
3.2 From set theory to probability

4. Probability distributions
4.1 Random variable
4.2 Random vectors and joint distributions
4.3 Marginal distributions
4.4 Conditional density function
4.5 Independent random variables
4.6 Expected value, moments, and co-moments
4.7 Discrete distributions
4.8 Continuous distributions

5. Random sampling
5.1 Sample statistics
5.2 Large-sample theory

6. Point and interval estimation
6.1 Point estimation
6.2 Interval estimation

7. Hypothesis testing
7.1 Rejection region for sample means
7.2 Size, level, and power of a test
7.3 Interpreting p-values
7.4 Likelihood-based tests

Author's website
webspace.qmul.ac.uk/mfernandes/