Explanatory statistics is also called inferential statistics or statistical induction and deals with inferences about the population from the characteristics of a random sample, i.e., with making (probability) statements about usually unknown parameters of a population. For instance, when taking a random sample (e.g., n = 1,000) of television viewers from the population of all
The original purpose of statistics was collecting data for government and administration. Thus, the term is used for, e.g., employment data or for censuses in general that provide data (statistics) about a population or nation. Scientifically, the term stands for different forms of presenting empirical data in charts, diagrams, or tables as well as for
A frequent goal of collecting data is to allow inferences to be drawn about a population from a sample. In such cases, inferential statistics provide the bases on which to draw such conclusions that go beyond the observed data. An example of a common inference is evaluating the likelihood that an observed effect (e.g., difference
Measurement provides a means for quantifying important phenomena of interest. In many measurement contexts, researchers are interested solely in efficiently describing the data. Descriptive statistics are the indexes through which such data summarization may be accomplished. Unlike contexts in which the researcher is interested in drawing generalizations from data, descriptive statistics are not used to