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.

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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.
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.
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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