Question

The dataset lists body masses in grams for 20 mammal species, and their corresponding base metabolic rate in Watts.

Copy the data into your preferred spreadsheet program, perform a natural log transform of both the base metabolic rates and the body masses of the mammals to improve the linear relationship, and then perform a linear regression on the data using the trendline feature.

Use the linear regression equation to estimate (based on these data) what the base metabolic rate of a human of 39.19 kilograms is likely to be.

Some hints and suggestions:

Remember that your variables have been transformed, so you will need to account for this as you find the base rate in Watts.

When answering, input only digits, with no spaces, and round to two decimal places.

Mammal Size (kg)	Base Metabolism (Watts)
4.67	11.57
1.02	2.56
0.206	0.73
0.19	0.86
0.105	0.55
0.3	1.1
61.235	61.16
0.2615	1.2
1.039	2.93
0.061	0.42
0.2615	1.2
127.006	105.34
70	82.78
2.33	4.2
1.3	1.73
9.5	16.05
1.011	2.07
0.225	1.3
0.8	4.39
102.058	89.55

Answer 1

The following is the R-code you need to do the necessary log transformation and fitting the least sqaure linear regression model. Codes are well-documented.

# Taking log for both the response and predictor variable

Lweight<-log(basal$weight)
LBM<-log(basal$BM)
length(LBM) # Number of observations

# Fitting linear regression model with the transformed variable

fit<-lm(LBM~Lweight)

# Estimating the basal metabolism for human with weight 39.19 kg

new <- data.frame(Lweight =log(39.19))
estimated.BM<-exp(predict(fit,new))
estimated.BM

The estimate is 44.03 watts