Bivariate Data

We wish to emphasize that the data sets presented so far are associated with a single random variable. This means that each sample refers to a single, specific population or population characteristic. The technical name for such data is univariate. Data which derives from two separate populations or population characteristics is called bivariate.

Conditional Probability: Part 2

The conditional probability of event B given that event A has occurred, P(B/A), was introduced in Chances Are…?. Here we provide additional examples of conditional probability with a special emphasis on applications of the general multiplication rule P(A and B) = P(A) x P(B/A), An extension of the general multiplication rule {P(A and B) = Read more about Conditional Probability: Part 2[…]

Some Distribution Theory

Here we outline some of the theory behind the chi-square, t- and F-distributions. Recall from Inferential Statistics that the chi-squared test uses the chi-squared statistic to determine whether or not two population characteristics are related in some way. While a large value for the chi-squared statistic suggests that the two characteristics are not independent, a Read more about Some Distribution Theory[…]

Inferential Statistics

As we saw in Statistics Defined, inferential statistics may be defined as the science of data interpretation. Data interpretation involves drawing one or more conclusions about a population underlying a data set accompanied by statements about the reliability of such conclusions. The process begins with a claim about some numerical feature of a population (a Read more about Inferential Statistics[…]