Book Your slot
X
ONLINE BOOKING
BOOK NOW
OFFLINE BOOKING
Call or WhatsApp 7993732682 (WhatsApp Now), 9177341827 (WhatsApp Now)
search
Menu Login home
  • Questions

  • Library

  • University Updates

  • Informatives

  • Technology Lines

  • Training & Internships

  • X
    Menu
  • Home
  • Privacy Policy
  • Legal Disclaimer
  • Terms & Conditions
  • Return Policy
  • About Us
  • Need any help?? write to us at

    support@engineershub.in

    Follow Us

    X
    LOGIN
    Login to access posts, links, updates, question papers, materials, one liners!
    Use Your Email Address/Mobile and Password to Login
    Forgot Password?
    Not a member? Sign Up
    LOGIN WITH EMAIL/MOBILE
    Forgot Password?
    Go Back
    FORGOT PASSWORD
    Go Back
    RESET PASSWORD
    Go Back
    Continue with LinkedIn
    OR
    Fill Up a Simple Form
    Already a Member? Login
    SIGN UP
    Fill all the below details correctly and click on Next
    Go Back
    Explain Chi-Squared test to detect outlier? - EngineersHub
    Go Back
    Question
    Anvesh Kanchibhotla
    2 years ago
    1 Answer(s) posted Write an answer 1889
    Answer
    Read Mode
    Answer posted by Ruchitha
    2 years ago

    Chi-squared test for outlier:
    Description:

    • Performs a chi squared test for detection of one outlier in a vector.

    Usage:

    • chisq.out.test(x, variance=var(x), opposite = FALSE)

    Arguments:

    • x: a numeric vector for data values.

    Variance: known variance of population. if not given, estimator from sample is taken, but there is not so much sense in such test (it is similar to z-scores)

    Opposite: a logical indicating whether you want to check not the value with largest difference from the mean, but opposite (lowest, if most suspicious is highest etc.).

    Details:


    This function performs a simple test for one outlier, based on chisquared distribution of squared differences between data and sample mean. It assumes known variance of population. It is rather not recommended today for routine use, because several more powerful tests are implemented.

    Examples

    • set.seed(1234)

    • x = rnorm(10)

    • chisq.out.test(x)

    • chisq.out.test(x,opposite=TRUE)

    Note:

    • This test is known to reject only extreme outliers, if no known variance is specified.

    Users Joined

    Srinivas
    1 day ago
    Challagali Kavya
    2 days ago
    Caroline Ocharo
    5 days ago
    narendra
    5 days ago
    Ananya
    6 days ago
    X
    Explain Chi-Squared test to detect outlier?
    X
    Explain Chi-Squared test to detect outlier?

    Chi-squared test for outlier:
    Description:

    • Performs a chi squared test for detection of one outlier in a vector.

    Usage:

    • chisq.out.test(x, variance=var(x), opposite = FALSE)

    Arguments:

    • x: a numeric vector for data values.

    Variance: known variance of population. if not given, estimator from sample is taken, but there is not so much sense in such test (it is similar to z-scores)

    Opposite: a logical indicating whether you want to check not the value with largest difference from the mean, but opposite (lowest, if most suspicious is highest etc.).

    Details:


    This function performs a simple test for one outlier, based on chisquared distribution of squared differences between data and sample mean. It assumes known variance of population. It is rather not recommended today for routine use, because several more powerful tests are implemented.

    Examples

    • set.seed(1234)

    • x = rnorm(10)

    • chisq.out.test(x)

    • chisq.out.test(x,opposite=TRUE)

    Note:

    • This test is known to reject only extreme outliers, if no known variance is specified.

    EngineersHub Logo
    x
    Loading...