Descriptive statistics are most often concerned with two sets of properties of a distribution (sample or population): central tendency (or location) seeks to characterize the distribution's central or typical value, while dispersion (or variability) characterizes the extent to which members of the distribution depart from its center and each other. Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors, sampling variation). In contrast, an observational study does not involve experimental manipulation. An experimental study involves taking measurements of the system under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements. Representative sampling assures that inferences and conclusions can reasonably extend from the sample to the population as a whole. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey samples. Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. Statistics (from German: Statistik, orig.
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