descriptive statistics

(noun)

A branch of mathematics dealing with summarization and description of collections of data sets, including the concepts of arithmetic mean, median, and mode.

Related Terms

  • bias
  • inferential statistics
  • null hypothesis

Examples of descriptive statistics in the following topics:

  • Descriptive or Inferential Statistics?

    • Descriptive statistics and inferential statistics are both important components of statistics when learning about a population.
    • Descriptive statistics is the discipline of quantitatively describing the main features of a collection of data, or the quantitative description itself.
    • Descriptive statistics are distinguished from inferential 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.
  • Descriptive Statistics

    • Descriptive statistics are numbers that are used to summarize and describe data.
    • Descriptive statistics are just descriptive.
    • Here we focus on (mere) descriptive statistics.
    • Some descriptive statistics are shown in Table 1.
    • For more descriptive statistics, consider Table 2.
  • Distorting the Truth with Descriptive Statistics

    • Descriptive statistics can be manipulated in many ways that can be misleading, including the changing of scale and statistical bias.
    • Descriptive statistics can be manipulated in many ways that can be misleading.
    • Bias is another common distortion in the field of descriptive statistics.
    • Descriptive statistics is a powerful form of research because it collects and summarizes vast amounts of data and information in a manageable and organized manner.
    • To illustrate you can use descriptive statistics to calculate a raw GPA score, but a raw GPA does not reflect:
  • Univariate descriptive statistics

    • As with any descriptive statistics, the scale of measurement (binary or valued) does matter in making proper choices about interpretation and application of many statistical tools.
    • The data that are analyzed with statistical tools when we are working with network data are the observations about relations among actors.
    • What we would like to summarize with our descriptive statistics are some characteristics of the distribution of these scores.
    • No statistics on distributional shape (skew or kurtosis) are provided by UCINET.
    • Univariate descriptive statistics for Knoke information and money whole networks
  • Lab: Descriptive Statistics

  • Applications of Statistics

    • This is called descriptive statistics .
    • Descriptive statistics and analysis of the new data tend to provide more information as to the truth of the proposition.
    • This data can then be subjected to statistical analysis, serving two related purposes: description and inference.
    • Descriptive statistics summarize the population data by describing what was observed in the sample numerically or graphically.
    • In descriptive statistics, summary statistics are used to summarize a set of observations, in order to communicate the largest amount as simply as possible.
  • Descriptive and Correlational Statistics

    • Descriptive and correlational statistics help interpret the relationship, or relatedness, between observable variables.
    • Descriptive and correlational statistics are used in psychology to describe data and illustrate the results.
    • As the name suggests, descriptive statistics describe how the data looks.
    • These statistics are not used to make any inferences from the collected data in relation to any population outside of the sample group.
    • Tools used for descriptive statistics include quantitative measures such as the mean, median, and mode, as well as a distribution curve.
  • Introduction to describing one network

    • Most social scientists have a reasonable working knowledge of basic univariate and bivariate descriptive and inferential statistics.
    • The application of statistics to social networks is also about describing distributions and relations among distributions.
    • Most of the descriptive statistical tools are the same for attribute analysis and for relational analysis -- but the subject matter is quite different!
    • Instead, alternative numerical approaches to estimating standard errors for network statistics are used.
    • So, let's begin with the simplest univariate descriptive and inferential statistics, and then move on to somewhat more complicated problems.
  • What Is Statistics?

    • In short, statistics is the study of data.
    • It includes descriptive statistics (the study of methods and tools for collecting data, and mathematical models to describe and interpret data) and inferential statistics (the systems and techniques for making probability-based decisions and accurate predictions based on incomplete data).
    • Statistics itself also provides tools for predicting and forecasting the use of data and statistical models.
    • Statistical methods date back at least to the 5th century BC.
    • In this book, Al-Kindi provides a detailed description of how to use statistics and frequency analysis to decipher encrypted messages.
  • Statistical Literacy

    • The experiment is described here: http://www.sciencenews.org/view/generic/id/333911/description/Saffron_takes_on_cancer.
    • What method could be used to test whether this difference between the experimental and control groups is statistically significant?
Subjects
  • Accounting
  • Algebra
  • Art History
  • Biology
  • Business
  • Calculus
  • Chemistry
  • Communications
  • Economics
  • Finance
  • Management
  • Marketing
  • Microbiology
  • Physics
  • Physiology
  • Political Science
  • Psychology
  • Sociology
  • Statistics
  • U.S. History
  • World History
  • Writing

Except where noted, content and user contributions on this site are licensed under CC BY-SA 4.0 with attribution required.