Skip to ContentGo to accessibility pageKeyboard shortcuts menu
OpenStax Logo
Statistics

Key Terms

StatisticsKey Terms

coefficient of correlation
a measure developed by Karl Pearson during the early 1900s that gives the strength of association between the independent variable and the dependent variable;
r= n xy[ x][ y] (n x 2 [ x] 2 )(n y 2 [ y] 2 ) r= n xy[ x][ y] (n x 2 [ x] 2 )(n y 2 [ y] 2 )
where n is the number of data points
The coefficient cannot be more than 1 and less than –1. The closer the coefficient is to ±1, the stronger the evidence of a significant linear relationship between x and y.
outlier
an observation that does not fit the rest of the data
Citation/Attribution

This book may not be used in the training of large language models or otherwise be ingested into large language models or generative AI offerings without OpenStax's permission.

Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute Texas Education Agency (TEA). The original material is available at: https://www.texasgateway.org/book/tea-statistics . Changes were made to the original material, including updates to art, structure, and other content updates.

Attribution information
  • If you are redistributing all or part of this book in a print format, then you must include on every physical page the following attribution:
    Access for free at https://openstax.org/books/statistics/pages/1-introduction
  • If you are redistributing all or part of this book in a digital format, then you must include on every digital page view the following attribution:
    Access for free at https://openstax.org/books/statistics/pages/1-introduction
Citation information

© Apr 16, 2024 Texas Education Agency (TEA). The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.