Descriptive Statistics Task
(Redirected from descriptive statistics)
- See: Retrospective Data Analysis, Statistical Population, Central Tendency, Statistical Dispersion, Skewness, Summary Statistic, Statistical Inference, Inductive Statistics, Sample Statistic, Statistical Population, Sample Size, Demographic, Comorbidity, Central Tendency, Statistical Dispersion, Mean.
- (Wikipedia, 2016) ⇒ https://en.wikipedia.org/wiki/Descriptive_statistics Retrieved:2016-8-3.
- Descriptive statistics is the discipline of quantitatively describing the main features of a collection of information, or the quantitative description itself. Descriptive statistics are distinguished from inferential statistics (or inductive statistics), in that descriptive statistics aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent. This generally means that descriptive statistics, unlike inferential statistics, are not developed on the basis of probability theory. Even when a data analysis draws its main conclusions using inferential statistics, descriptive statistics are generally also presented. For example in a paper reporting on a study involving human subjects, there typically appears a table giving the overall sample size, sample sizes in important subgroups (e.g., for each treatment or exposure group), and demographic or clinical characteristics such as the average age, the proportion of subjects of each sex, and the proportion of subjects with related comorbidities. Some measures that are commonly used to describe a data set are measures of central tendency and measures of variability or dispersion. Measures of central tendency include the mean, median and mode, while measures of variability include the standard deviation (or variance), the minimum and maximum values of the variables, kurtosis and skewness.
- Investopedia, Descriptive Statistics Terms
- (AMTA, 2010) ⇒ American Massage Theory Association. (2010). “Glossary of Research Terminology."
- QUOTE: Descriptive Statistics: The family of quantitative analysis techniques that allows one to characterize, portray, or literally describe a data set in succinct and economical ways.