The `linregress()` method in the scipy module is used to fit a simple linear regression model using "Reaction" (reaction time) as the response variable and "Drinks" as the predictor variable. The output is shown below. What is the correct regression equation based on this output? Is this model statistically significant at a 5% level of significance (alpha = 0.05)? Select one.```LinregressResult(slope=6.000000000000001, intercept=3.999999999999964, rvalue=0.972816652688823, pvalue=0.001098352017795293, stderr=0.7141428428542851)```Options:- ⭕ Reaction = 6.0000 + 3.9999 Drinks, model is not statistically significant- ⭕ Reaction = 3.9999 + 6.0000 Drinks, model is statistically significant- ⭕ Reaction = 6.0000 + 3.9999 Drinks, model is statistically significant- ⭕ Reaction = 3.9999 + 6.0000 Drinks, model is not statistically significantThe output indicates the model's slope and intercept values along with statistical metrics:- **Slope**: 6.0000- **Intercept**: 3.9999- **r-value**: 0.9728 (indicates a strong positive correlation)- **p-value**: 0.0011 (less than 0.05, suggesting statistical significance)- **Standard error**: 0.7141The correct regression equation is: **Reaction = 3.9999 + 6.0000 Drinks**Since the p-value is less than 0.05, the model is statistically significant.

Given that Level of significance =alpha =0.05

Answered: Listen The linregress() method in scipy…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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