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Richard Waterman discusses correlation, simple regressions, and how to interpret regression coefficients. Correlation is the measure of the linear association between X and Y. Waterman explains the importance of correlation, regression, and the best fit line.

Correlation (Statistics) --- Regression analysis. --- Commercial statistics.

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Richard Waterman discusses covariance and portfolios. Covariance is the measure of dependence between two random variables. Waterman explains how to calculate the covariance and the performance of portfolios.

Analysis of covariance. --- Commercial statistics. --- Research --- Statistical methods.

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In part 2 of his series on business mathematics, Professor Richard Waterman explains probability and when it can be useful. Probability is used when there is some form of uncertainty in the research question. Waterman discusses probability in the real world, notation in probability, and how to calculate probability.

Commercial statistics. --- Probabilities.

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In the fourth section of this series on quantitative modeling, Professor Richard Waterman discusses one-number summaries and calculating predictions in models with normal distributions. He provides insight on how the different models work and when one would work better than the other.

Regression analysis. --- Research --- Statistical methods.

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In part 2.4 of his series on business mathematics, Professor Richard Waterman explains statistics and confidence intervals. A confidence interval is a range of feasible values for an unknown population parameter. Waterman also discusses the central limit theorem and using the confidence interval to make a decision about data.

Commercial statistics.