Saturday, August 18, 2012


As you start the study of statistics, you will find topics and equations that you have studied in previous classes.  Mean-median-mode, for example, should quickly bring to mind average-middlemost-most frequent.  Other familiar terms have unique definitions for statistics class.  Meanings aren’t as much “different” as they are more “specific” and carry definite implications. 

What follows is not a complete list, but rather a sampling of the vocabulary with explicit meanings in the course.  There are only 10 here to get you started and a suggestion for continuing to prepare for AP Stats on your own.

Population: The complete set of data elements is termed the population.

Sample: A sample is a portion of a population selected for further analysis.

Parameter: A parameter is a characteristic of the whole population.

Statistic: A statistic is a characteristic of the sample.

                 Notice that the P’s are associated with each other and 
                 the S’s are associated with each other:  
                 Parameter is to Population as Statistic is to Sample

Individual refers to the elements in a set

Variable refers to the characteristics describing individual elements of a set.

Qualitative data are non-numeric or categorical data.

Quantitative data are numeric and can be either Discrete or Continuous.

     Discrete: numeric data that have a finite number of possible values.  When opinion surveys evaluate answers like “Strongly disagree, Disagree, Neither disagree or agree, Agree, Strongly agree, each possible answer is given a discrete numeric value so meaningful statistical computations can be made.  The same information could be gathered through options like “on a scale of 1 to 5...”

Data counts are always discrete: for example, the number of students enrolled in your statistics classes.

     Continuous: numeric data that have infinite possibilities: the set of all counting numbers or the set of all real, rational numbers between 1 and 2.

If you already have your textbook, look at the glossary to find other terms that you've run into before.  Read definitions to identify how these words might be similar and/or different from your past encounters with them. 

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