Jump to content

Search the Community

Showing results for tags 'regression'.



More search options

  • Search By Tags

    Type tags separated by commas.
  • Search By Author

Content Type


Forums

  • Learning Business Excellence and Lean Six Sigma
    • Coronavirus Discussions
    • Lean Six Sigma for Beginners
    • Lean Six Sigma applicability in Industry Sectors
    • Discussion Forum for Practitioners
    • Bench and Mark Cartoons
    • Debate : For or Against
  • Six Sigma Practice Project for Benchmark Participants
    • Six Sigma Practice Project - all updates
    • Enrolling for Practice Project
    • Did not get email from Academy?
    • Working with Phases of Practice Project
    • Registering and participating in webinars
  • Know about Benchmark Six Sigma
    • About Us, Services, Recognition, Network, Support
  • Recreation and Discussion Center
    • Debate Halls
    • Fun and Trivia
    • Benchmark Six Sigma Cartoon Strip
    • We ask and you answer! The best answer wins.
  • Discussions related to Training
    • Discussions related to Green Belt, Black Belt, Lean Expert
    • Right Sequence for Training and Projects
    • Master Black Belt and its competencies
    • Refresh your basics on data analysis
  • Benchmark Six Sigma Participants Support Forum
    • Post Workshops Guidelines
    • Career & Project Discussions
    • Lean Six Sigma Discussions
  • Articles from across the Globe
  • You ask and we answer!

Categories

  • Process Excellence
  • Data Driven Decision Making
  • Debate

Blogs

There are no results to display.

There are no results to display.

Categories

  • Participants Support- General
  • Open Forum- General
  • Basic Maths for Six Sigma
  • Training Brochures
  • Black Belt Pre-Study Material & Exercise Content
  • Green Belt Pre-Study Material & Exercise Content
  • Dorf Ketal Green Belt Pre-Study Material & Exercise Content
  • Kidambi - Black Belt Pre-Study Material & Exercise Content
  • Willis Tower Watson Black Belt Exercise Content Copy
  • Online Green Belt
  • Online Black Belt

Calendars

There are no results to display.

There are no results to display.


Find results in...

Find results that contain...


Date Created

  • Start

    End


Last Updated

  • Start

    End


Filter by number of...

Joined

  • Start

    End


Group


Mobile


Name


Company


Designation


Industry


Function


Birth Year


Interests


GB Score


GB Certificate Issue Date


GB Certificate Expiry Date


BB Certificate No


BB Certificate Issue Date


BB Certificate Expiry Date


LMC Certificate No


LMC Certificate Issue Date


MBB Certificate No


MBB Certificate Issue Date


Batch Number


GB Batch Code


BB Batch Code


LMC Batch Code


MBB Batch Code


RABQSA Batch Code (GB)


RABQSA Batch Code (BB)


GB Project


GB Project Issue Date


GB Project Certificate No


BB Project


BB Project Issue Date


BB Project Certificate No


MBB Project


MBB Project Issue Date


MBB Project Certificate No


BB Score


LMC Score


MBB Score

Found 8 results

  1. Q 286. Why is multicollinearity a problem? How is it detected? What is the right course of action when it is found? Explain with an example. Note for website visitors - Two questions are asked every week on this platform. One on Tuesday and the other on Friday. All questions so far can be seen here - https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/ Please visit the forum home page at https://www.benchmarksixsigma.com/forum/ to respond to the latest question open till the next Tuesday/ Friday evening 5 PM as per Indian Standard Time. Questions launched on Tuesdays are open till Friday and questions launched on Friday are open till Tuesday. The best answer is always shown at the top among responses and the author finds honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term
  2. Q 271. What is a residual in Regression? Why is it important to analyze the residuals before assessing the goodness of a Regression Model? What does it mean if Residuals are non normal or non random? Note for website visitors - Two questions are asked every week on this platform. One on Tuesday and the other on Friday. All questions so far can be seen here - https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/ Please visit the forum home page at https://www.benchmarksixsigma.com/forum/ to respond to the latest question open till the next Tuesday/ Friday evening 5 PM as per Indian Standard Time. Questions launched on Tuesdays are open till Friday and questions launched on Friday are open till Tuesday. The best answer is always shown at the top among responses and the author finds honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term
  3. Q 232. Quantile Regression estimates the median (or a particular quantile) whereas Linear Regression estimates the mean. What are some of the business scenarios where quantile regression would yield better results as compared to linear regression? Note for website visitors - Two questions are asked every week on this platform. One on Tuesday and the other on Friday. All questions so far can be seen here - https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/ Please visit the forum home page at https://www.benchmarksixsigma.com/forum/ to respond to the latest question open till the next Tuesday/ Friday evening 5 PM as per Indian Standard Time The best answer is always shown at the top among responses and the author finds honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term
  4. What are the key differences between Multiple Regression using historical data and Multiple Regression based on Experimental Data (DOE)? What are the advantages of one over the other, if at all?
  5. Q. 145 What is the usage of R Squared and R Squared Adjusted as used in Regression Analysis. Please explain with example(s).  Note for website visitors - Two questions are asked every week on this platform. One on Tuesday and the other on Friday. All questions so far can be seen here - https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/ Please visit the forum home page at https://www.benchmarksixsigma.com/forum/ to respond to the latest question open till the next Tuesday/ Friday evening as per Indian Standard Time. The best answer is always shown at the top among responses and the author finds honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term.
  6. i am doing ordinal logistic regression using minitab, please find the results as below. when i asked my friend to cross check the results in "R" for the same data set, i was surprised to see different results come up. what was even more peculiar is that the coef no's seem to be similar however Minitab was showing -ve values where "R" was throwing +ve values and vice versa. i am curious to know why this happens and which result should i consider? Coedf(Minitab) Coef( r ) overall Rating -2.86% 2.86% Parameter (A) 1.30% -1.30% Parameter ( 9.24% -9.24% Parameter © 7.11% -7.16% Parameter(D) 6.79% -6.79% Raw data as below..( overall rating = Y, Parameters(A,B,C,D,E)=X's) Rating Scale of (1-5), 1 being lowest, 5 being highest Overall Rating Parameter(A) Parameter( Parameter( C ) Parameter (D) Parameter ( E ) 2 4 1 5 4 5 2 3 3 4 1 2 3 1 2 5 1 2 5 5 1 4 5 2 4 2 3 4 2 5 5 2 2 3 5 4 1 5 5 4 4 3 2 1 5 1 2 5 1 4 2 4 1 4 4 1 3 4 4 1 2 2 1 3 1 4 1 5 3 4 5 4 4 5 5 2 5 4 3 1 1 2 5 5 4 2 1 2 3 5 5 5 3 1 3 5 5 4 1 2 4 3 2 5 3 2 3 2 3 3 2 2 3 4 1 3 2 5 2 3 1 3 1 5 4 5 3 2 2 4 3 2 5 2 2 4 1 5 4 3 1 1 1 4 3 3 4 1 1 4 2 5 4 3 3 5 3 5 4 2 2 3 4 5 1 3 1 3 5 1 1 4 4 3 5 5 2 2 4 5 5 5 5 4 2 2 4 1 5 1 3 3 3 2 3 3 2 2 3 5 3 1 5 4 1 1 1 2 4 5 5 4 1 2 4 1 1 5 5 5 5 4 5 2 5 3 3 1 5 5 4 5 2 3 5 2 5 4 3 3 4 2 1 3 3 4 4 1 5 2 3 3 2 4 5 3 5 4 5 4 2 1 1 2 3 2 4 4 2 5 4 2 1 5 1 5 5 2 1 5 1 5 2 3 3 2 3 5 1 3 2 4 4 3 1 1 2 3 4 2 1 3 3 1 3 5 2 2 5 2 3 5 2 3 5 5 3 4 2 2 1 1 4 5 5 2 4 1 2 3 1 5 5 2 1 4 1 5 4 5 2 3 1 4 1 3 4 5 1 3 5 2 1 1 4 1 5 4 4 5 2 2 1 1 2 4 1 1 4 1 1 3 2 1 4 3 3 1 5 5 2 3 1 4 3 5 3 3 2 4 3 4 5 3 3 4 2 5 1 2 1 2 3 5 1 1 1 5 1 1 2 3 3 1 2 4 4 4 3 4 2 3 5 1 4 4 1 4 2 4 3 3 5 1 5 1 3 1 1 2 5 2 4 1 5 3 2 3 5 3 1 5 4 1 5 4 1 5 1 3 2 4 2 1 4 4 1 4 1 2 1 5 5 2 4 2 3 2 5 1 1 2 2 1 5 1 4 2 5 3 2 5 1 1 2 1 1 2 5 5 4 1 3 5 3 1 3 1 1 5 2 2 5 3 5 5 4 2 1 4 1 5 3 2 1 3 5 2 5 4 5 3 3 2 4 5 4 2 4 5 1 4 2 4 1 5 1 2 3 4 5 5 3 4 5 3 2 4 4 3 3 4 2 5 4 4 1 3 5 2 1 2 3 2 2 5 3 5 3 1 4 3 3 3 4 5 1 4
  7. Hello Friends, Recently I have attended the interview with a six sigma expert, he give me scenario and told me to find the flaw in it. Below is scenario : When Age is increase and petrol price is also increasing, the tool used is regression. The result shows as strong positive correlation. R=1 What is the flaw?
  8. Hi, Here is a quick query.... If for a Logistic Regression Test, the Whole Model Test is significant (p<0.05) and the Lack of Fit test is also significant (p<0.05), with just one parameter, what should be our interpretation and next steps. I was using the test to validate one of the Xs. Nirankar
×
×
  • Create New...