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- If you have just collected the data, it is always a good
idea to look first at the appropriate summary statistics for each variable in the file.
For example, you may want to compute frequency distributions for all variables to identify
outliers.
- Usually, data are collected to test specific hypotheses or
models concerning some variables. For example, we may want to find out whether men are
more likely to agree with an item on a questionnaire than women. More complicated
hypotheses may pertain to the nature of relationships between variables, for example,
whether it is linear or non-linear.
- If you have no specific hypotheses, and the nature of the
study is exploratory, you may want to use some techniques that are designed to help 'make
sense' of the data, that is, to detect patterns, clusters, etc.
- The fourth option (quality control/improvement) will guide
you through the various techniques for industrial quality control, experimentation, and
reliability analysis.
- The techniques of statistical power analysis, sample size
estimation, and advanced techniques for confidence interval estimation
are discussed here. The main goal of first two techniques is to allow you to decide, while
in the process of designing an experiment, (a) how large a sample is needed to allow
statistical judgments that are accurate and reliable, (b) how likely your statistical test
will be to detect effects of a given size in a particular situation. The third technique
is useful in implementing objectives (a) and (b) above, and in evaluating the size of
experimental effects in practice.
- Entries in the Statistical Glossary are taken from the
Electronic Manual of STATISTICA and may contain elements that refer to specific
features of the STATISTICA system.
- As compared to probability calculators, the traditional format of distribution tables like those
presented here, has the advantage of showing simultaneously many values and thus allowing
the user to examine and quickly explore ranges of probabilities.
- StatSoft offers a variety of Enterprise-wide software solutions, including STATISTICA Enterprise-wide Data Mining System, STATISTICA Enterprise-wide Data Analysis System and STATISTICA Enterprise-wide SPC System.
- If you wish to explore large amounts of (typically
business or market related) data in search for consistent patterns and/or systematic
relationships between variables, and then to validate the findings by applying the
detected patterns to new subsets of data you may be looking for the popular Data Mining and Data Warehousing concepts.
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