MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Question
1.)The dataset above represents average height and weights for female babies at certain ages. For the dataset above, write the R code, that would do the following:
a.) Create a multilinear regression model that predicts a female baby's age based on both their weight and length.
b.)Gives a summary of the main features of your linear regression model which includes RSE, equation of regression line, R^2 and adj(R^2) values and plots the residuals.
c.) Predicts a female baby's age who weighs 20 pounds and is 28 inches long.
Expert Solution
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Step 1
a) R code for this sub question:
# Read the dataset
data <- read.csv("dataset.csv")
# Fit a multilinear regression model
model <- lm(Age_months ~ Weight_pounds + Length_inches, data = data)
# View the summary of the model
summary(model)
OUTPUT:
Call:
lm(formula = Age_months ~ Weight_pounds + Length_inches, data = data)
Residuals:
1 2 3 4 5 6
3.337 -2.023 0.281 -3.633 -2.501 4.540
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -36.8914 11.0622 -3.335 0.0446 *
Weight_pounds 0.2478 0.2852 0.869 0.4488
Length_inches 1.6364 0.5041 3.246 0.0476 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 4.296 on 3 degrees of freedom
Multiple R-squared: 0.9358, Adjusted R-squared: 0.893
F-statistic: 21.87 on 2 and 3 DF, p-value: 0.01626
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