Topic One

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Statistics is defined as a group of methods used to collect, analyze, present and interpret data in order to make decisions. There are two main types of statistics: descriptive and inferential statistics. If there are data to represent the scores of teams in a football league, the entire set of scores that represents the scores of the teams is called the data set.  The name of each football club is called an element and the scores of each football club are called the observation. Data sets in their original form are very large and are usually summarized in graphs, tables and ratios. The reduction of data in this manner to assist in decision making is called description statistics.

In statistics, the collection of elements of interested information is called the population; it is the entire data category.  However, this population is so large at times that a certain portion of this population is selected.  These selected portions are called the samples. The making of decisions from these samples is called inferential statistics.

Discrete variables are variables that can be counted and will assume a numerical value. On the other hand, continuous variables are those that do not have a specific numerical value but fall into a certain range. We therefore do not know with certainty the exact value of a particular number.

Time series data are data for a particular variable such as the inflation rate over a period of time.  For example, information on the inflation rate from 1990 to 2007 is called time series.  On the other hand, cross-section data are data on different elements such as inflation rate, unemployment rate, trade surplus and foreign reserves for one year.

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