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:
  • 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.
  • 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.
  • Tests of Significance

    • In relation to Fisher, statistical significance is a statistical assessment of whether observations reflect a pattern rather than just chance.
    • The probability of the data is normally reported using two related statistics:
    • The statistical significance of the results depends on criteria set up by the researcher beforehand.
    • The test statistics $z$ and $F$, on the other hand, do not provide immediate useful information, and any further interpretation needs of descriptive statistics.
    • Examine the idea of statistical significance and the fundamentals behind the corresponding tests.
  • Statistical Literacy

    • See the description of the results here: http://articles.latimes.com/2011/may/31/news/la-heb-niacin-cholesterol-20110531.
  • 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?
  • Statistical Literacy

    • Perhaps the fullest description was presented on the CNNMoney website (A service of CNN, Fortune, and Money) in an article entitled "Survey: iPhone retention 94% vs.
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