Loading [MathJax]/extensions/TeX/mhchem.js
Skip to main content
Library homepage
 

Text Color

Text Size

 

Margin Size

 

Font Type

Enable Dyslexic Font
Business LibreTexts

Search

  • Filter Results
  • Location
  • Classification
    • Article type
    • Cover Page
    • License
    • Show TOC
    • Transcluded
    • Author
    • OER program or Publisher
    • Autonumber Section Headings
    • License Version
  • Include attachments
Searching in
About 2 results
  • https://biz.libretexts.org/Workbench/MGT_235/06%3A_Confidence_Intervals/6.01%3A_Introduction
    The empirical rule, which applies to the normal distribution, says that in approximately 95% of the samples, the sample mean, \(\overline x\), will be within two standard deviations of the population ...The empirical rule, which applies to the normal distribution, says that in approximately 95% of the samples, the sample mean, \(\overline x\), will be within two standard deviations of the population mean \mu. Where \(\overline x\) is the sample mean. \(Z_{\alpha}\) is determined by the level of confidence desired by the analyst, and \(\sigma / \sqrt{n}\) is the standard deviation of the sampling distribution for means given to us by the Central Limit Theorem.
  • https://biz.libretexts.org/Courses/Gettysburg_College/MGT_235%3A_Introductory_Business_Statistics_(2nd_edition)/06%3A_Confidence_Intervals/6.01%3A_Introduction
    The empirical rule, which applies to the normal distribution, says that in approximately 95% of the samples, the sample mean, \(\overline x\), will be within two standard deviations of the population ...The empirical rule, which applies to the normal distribution, says that in approximately 95% of the samples, the sample mean, \(\overline x\), will be within two standard deviations of the population mean \(\mu\). Where \(\overline x\) is the sample mean. \(z_\frac{\alpha}{2}\) is determined by the level of confidence (1-\(\alpha\)) desired by the analyst, and \(s / \sqrt{n}\) is the standard deviation of the sampling distribution for means given to us by the Central Limit Theorem.

Support Center

How can we help?