Descriptive Statistics and Discrete Probability Distributions

Edward B. Magrab
Additional contact information
Edward B. Magrab: University of Maryland

Chapter Chapter 1 in Engineering Statistics, 2022, pp 1-27 from Springer

Abstract: Abstract In this chapter, we introduce several fundamental aspects of statistics: its language, quantities used to describe data, visualization of data, discrete probability distributions, and terms that describe measurements. For the language of statistics, we define such terms as experiments, random samples, bias, and probability. For the quantities that describe data, we define the mean, median, mode, quartiles, expected value, unbiased variance, and covariance. For visualizing data, we discuss histograms, box-whisker plots, and scatter plots. Discrete probability distributions, the cumulative frequency function, the probability mass function, and the binomial distribution and the Poisson distribution are defined. Then, the concept of independent random variables and its significance is discussed. Lastly, terms used to describe measurements are defined and illustrated: accuracy, precision, repeatability, reproducibility, and stability.

Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-05010-7_1

Ordering information: This item can be ordered from
http://www.springer.com/9783031050107

DOI: 10.1007/978-3-031-05010-7_1

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().