5.2 - Interval Estimate of Population Mean.5.1 - Distribution of Sample Mean Vector.Lesson 5: Sample Mean Vector and Sample Correlation and Related Inference Problems.4.7 - Example: Wechsler Adult Intelligence Scale.4.6 - Geometry of the Multivariate Normal Distribution.4.4 - Multivariate Normality and Outliers.4.3 - Exponent of Multivariate Normal Distribution.Lesson 4: Multivariate Normal Distribution.Lesson 3: Graphical Display of Multivariate Data.Lesson 2: Linear Combinations of Random Variables.1.5 - Additional Measures of Dispersion.Lesson 1: Measures of Central Tendency, Dispersion and Association.We do not necessarily think of one set of variables as independent and the other as dependent, though that may potentially be another approach. One approach to studying relationships between the two sets of variables is to use canonical correlation analysis which describes the relationship between the first set of variables and the second set of variables. We may wish to explore the relationships between the sales performance variables and the aptitude variables. may be measured and a second set of variables on environmental toxins are measured, such as the concentrations of heavy metals, pesticides, dioxin, etc.įor a third example consider a group of sales representatives, on whom we have recorded several sales performance variables along with several measures of intellectual and creative aptitude. Two types of variables are measured and the relationships between the exercise variables and the health variables are of interest.Īs a second example consider variables measured on environmental health and environmental toxins. A number of environmental health variables such as frequencies of sensitive species, species diversity, total biomass, the productivity of the environment, etc. On the other hand, you have variables that attempt to measure overall health, such as blood pressure, cholesterol levels, glucose levels, body mass index, etc. On the one hand, you have variables associated with exercise, observations such as the climbing rate on a stair stepper, how fast you can run a certain distance, the amount of weight lifted on a bench press, the number of push-ups per minute, etc. Canonical correlation analysis explores the relationships between two multivariate sets of variables (vectors), all measured on the same individual.Ĭonsider, as an example, variables related to exercise and health.
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