Can Categorical Variables be Used in Multiple Regression Models?

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SUMMARY

The discussion centers on the use of categorical variables in multiple regression models, specifically in the context of a regression equation involving grams of seed as the dependent variable (Y) and number of fruit (N), type of fruit (T), and field number (F) as independent variables. It is established that multiple linear regression requires all independent variables to be quantitative, thus excluding categorical variables like type of fruit from direct inclusion in the model. The user attempted to set up this model in Minitab but faced challenges due to the categorical nature of the type variable.

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smp
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Hello, I am trying to do the following regression model;

Y = N + T + F + NT + NF + NTF + error

Y= Grams of seed
N= Number of fruit
T= Type of fruit (2 types, alpha)
F= Field number (3)

I have tried putting this in MiniTab and I can't get this set up correctly.
Assistant> Regression> Multiple Regression

Y= Grams of Seed

Continuous X Variable= Number of Fruit, Field Number - but I can't select Type since they are words and not numbers. .

Categorical X value is optional- should I put Type here?

Thank You
 
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Hi smp, welcome to MHB!

This looks like a trick question.
We can indeed not add a type and number together. That is, it is not possible to evaluate something like "apple" + 2.
More generally, a multiple linear regression requires that all variables are quatitative (interval or ratio). That excludes categorical.
 

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