2. Descriptive Statistics

The following sections describe how to obtain basic descriptive statistics (i.e. just summarize data, without drawing any formal conclusions) for three common data formats: one-sample data; k-sample data; and correlation-regression data:
2.1. One Sample Data : The simplest possible data model. One column of data x1, x2, ..., xn.

A few examples: maximum heart rates of n=11 parachutists; the number of homeless for each of n=22 US cities; skull widths of n=84 Etruscan skulls; etc.

2.2. 2-Sample Data: Two sets of independent samples x1,...,xn and y1,..., ym, representing two different treatments X and Y. The objective is to compare the effects of the two treatments.

Examples: First walking times x1,...,x7 for n=7 babies who go through an ``active exercise'' program, and first walking times y1,...,y6 for m=6 babies who go through a ``passive exercise'' program; etc.

2.3. Paired Sample Data: Similar to 2-sample data, but comparing the two samples are dependent.

2.4. k-Sample Data: Like 2-sample data, but comparing k>2 treatments.

2.5. Regression-correlation data: Two dissimilar measurements x and y are taken on each of n subjects: (x1,y1), (x2,y2), ..., (xn,yn). The objective is to quantify the relationship between the two measurements x and y.

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Last modified 12/1/95