Effect size is a statistical
concept that measures the strength of the relationship between two
variables on a numeric scale.
Statistic effect size helps us in
determining if the difference is real or if it is due to a change
the effect size is usually
measured in three ways: (1) standardized mean difference, (2) odd
ratio, (3) correlation coefficient.
confidence interval, in
statistics, refers to the probability that a population parameter
will fall between two set values for a certain proportion of times.
Confidence intervals measure the degree of uncertainty or certainty
in a sampling method.
A confidence interval can take
any number of probabilities, with the most common being a 95% or
99% confidence level.
Statisticians use confidence
intervals to measure uncertainty.