Fitting Two Lines with Minitab: A Beginner's Guide

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  • Thread starter Thread starter Niall101
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SUMMARY

This discussion focuses on fitting two lines using Minitab for a scatterplot where Y is defined as 2*X + eps. The user seeks guidance on applying the least squares method for both Y = ax + b and X = cy + d equations. The correct procedure involves using Minitab's regression commands found under Stat --> Regression --> Regression, running the regression twice for each equation. Additionally, to create fitted line plots for both equations, the user should navigate to Stat --> Regression --> Fitted Line Plot.

PREREQUISITES
  • Basic understanding of linear regression concepts
  • Familiarity with Minitab software interface
  • Knowledge of scatterplot interpretation
  • Experience with least squares method
NEXT STEPS
  • Learn how to perform multiple regression analysis in Minitab
  • Explore Minitab's capabilities for creating fitted line plots
  • Study the implications of reversing predictor and response variables
  • Investigate advanced regression techniques in Minitab, such as polynomial regression
USEFUL FOR

This discussion is beneficial for beginners in data analysis, specifically those using Minitab for regression analysis, as well as educators teaching statistical methods and practitioners needing to visualize relationships in data.

Niall101
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I have a scatterplot X is just 30 given values. Y is 2*X + eps, where eps is a random figure. The Plot is Y vs X

I am asked to fit 2 lines

Y= ax +b by least squared method

and

X = cy +d

Similarly

I do not know which command to use on minitab. Is this just standard regression? if so how do I fit the X = cy +d line. is there any difference?

Do I just use the fitted line plot? and if so how do i plot X = cy +d on the same graph??

Thanks in advance! ( and sorry if this is very basic I am new to minitab)
 
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The regression command in Minitab can be found with this sequence of menu steps:

Stat --> Regression --> Regression

You will be asked to specify the response and predictor variables. Run the regression procedure twice - once with Y as response and x as predictor, the second time with the roles reversed.

If all you want is the fitted line plot (two of them, one for each of your cases)

Stat --> Regression --> Fitted Line Plot

and follow the same idea for specifying variables.
 

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