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.
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.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
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.

Transcribed Image Text:Age_months
0
3
9
15
20
36
Weight_pounds
7.3
13.3
18.8
22
24.4
31.5
Length_inches
19.4
23.6
27.6
30.6
32.6
37
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:
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.
a.) Create a multilinear regression model that predicts a
female baby's age based on both their weight and length.
c.) Predicts a female baby's age who weighs 20 pounds and
is 28 inches long.
Expert Solution

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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