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Information on statistics:
Statistics is a mathematical science pertaining to the
collection, analysis, interpretation or explanation, and presentation
of data. It also provides tools for prediction and forecasting based on
data. It is applicable to a wide variety of academic disciplines, from
the natural and social sciences to the humanities, government and business.
Statistical methods can be used to summarize or describe
a collection of data; this is called descriptive statistics. In addition,
patterns in the data may be modeled in a way that accounts for randomness
and uncertainty in the observations, and are then used to draw inferences
about the process or population being studied; this is called inferential
statistics. Descriptive, predictive, and inferential statistics comprise
applied statistics.
There is also a discipline called mathematical statistics,
which is concerned with the theoretical basis of the subject. Moreover,
there is a branch of statistics called exact statistics that is based
on exact probability statements.
The word statistics can either be singular or plural. In its singular
form, statistics refers to the mathematical science discussed in this
article. In its plural form, statistics is the plural of the word statistic,
which refers to a quantity (such as a mean) calculated from a set of data.
In applying statistics to a scientific, industrial, or societal problem,
it is necessary to begin with a process or population to be studied. This
might be a population of people in a country, of crystal grains in a rock,
or of goods manufactured by a particular factory during a given period.
It may instead be a process observed at various times; data collected
about this kind of "population" constitute what is called a
time series.
For practical reasons, rather than compiling data about an entire population,
a chosen subset of the population, called a sample, is studied. Data are
collected about the sample in an observational or experimental setting.
The data are then subjected to statistical analysis, which serves two
related purposes: description and inference.
* Descriptive statistics can be used to summarize the data, either numerically
or graphically, to describe the sample. Basic examples of numerical descriptors
include the mean and standard deviation. Graphical summarizations include
various kinds of charts and graphs.
* Inferential statistics is used to model patterns in the data, accounting
for randomness and drawing inferences about the larger population. These
inferences may take the form of answers to yes/no questions (hypothesis
testing), estimates of numerical characteristics (estimation), descriptions
of association (correlation), or modeling of relationships (regression).
Other modeling techniques include ANOVA, time series, and data mining.
