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ata by the rest of the brain, particu scale up with the size of animals' sented differentially across specie for their body and cerebellums al

ata by the rest of the brain, particu scale up with the size of animals' sented differentially across specie for their body and cerebellums al

MATLAB: An Introduction with Applications
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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Find the equation for the regression line using the log-transformed values. 

Predict the cerebellum weight in grams of a species weighing 100,000 g (100 kg or about 220 lb). Make sure to transform the grams into log units first and then back into
grams for the prediction (remember that y = 10log(y)). Round your answer in grams to 2 decimal places.
 
4.30 (EX) The intriguing cerebellum. 1/5: The cerebellum is a highly convoluted brain structure siting underneath the cerebral hemispheres. This intriguing structure is thought to facilitate the acquisition and use of sensory data by the rest of the brain, particularly the motor areas. Studies suggest that the cerebellum may scale up with the size of animals' bodies and brains, whereas other parts of the brain are clearly represented differentially across species. Here are data on 15 mammal species showing the weight in grams for their body and cerebellums, along with the logarithm transformed values. ex04-30.xls Make a scatterplot of cerebellum weight (y) against body weight (x) and another scatterplot using the transformed values. Which two are the plots? Cerebellum weight Log(cerebellum weight) 160 140 120 100 80 60 40- 20 0 2.5 NN 50 0 2.0 1.5 1.0 0.5 0.0 -0.5- -1.0 -1.5 1 Scatterplot I 100,000 200,000 300,000 400,000 Body weight Scatterplot III 3 Log(body weight) 5 Cerebellum weight Log(cerebellum weight) 160 140 120 100 80 60 40 20 0 221 SOSOSOS S 2.5 2.0 1.5 1.0 0.5 0.0 -0.5- -1.0 0 -1.5 1 Scatterplot II 100,000 200,000 300,000 400,000 Body weight Scatterplot IV 3 Log(body weight) 5
Transcribed Image Text:4.30 (EX) The intriguing cerebellum. 1/5: The cerebellum is a highly convoluted brain structure siting underneath the cerebral hemispheres. This intriguing structure is thought to facilitate the acquisition and use of sensory data by the rest of the brain, particularly the motor areas. Studies suggest that the cerebellum may scale up with the size of animals' bodies and brains, whereas other parts of the brain are clearly represented differentially across species. Here are data on 15 mammal species showing the weight in grams for their body and cerebellums, along with the logarithm transformed values. ex04-30.xls Make a scatterplot of cerebellum weight (y) against body weight (x) and another scatterplot using the transformed values. Which two are the plots? Cerebellum weight Log(cerebellum weight) 160 140 120 100 80 60 40- 20 0 2.5 NN 50 0 2.0 1.5 1.0 0.5 0.0 -0.5- -1.0 -1.5 1 Scatterplot I 100,000 200,000 300,000 400,000 Body weight Scatterplot III 3 Log(body weight) 5 Cerebellum weight Log(cerebellum weight) 160 140 120 100 80 60 40 20 0 221 SOSOSOS S 2.5 2.0 1.5 1.0 0.5 0.0 -0.5- -1.0 0 -1.5 1 Scatterplot II 100,000 200,000 300,000 400,000 Body weight Scatterplot IV 3 Log(body weight) 5
Species Mouse Bat Flying Fox Pigeon Guinea Pig Squirrel Chinchilla Rabbit Hare Cat Dog Macaque Sheep Bovine Human Body 58 30 130 500 485 350 500 1,800 3,000 3,500 3,500 6,000 25,000 300,000 60,000 Cerebellum Log (body) Log (cerebellum) 1.76 1.48 2.11 2.70 2.69 2.54 2.70 3.26 3.48 3.54 3.54 3.78 4.40 5.48 4.78 0.09 0.09 0.30 0.40 0.90 1.50 1.70 1.90 2.30 5.30 6.00 7.80 21.50 35.70 142.00 -1.05 -1.05 -0.52 -0.40 -0.05 0.18 0.23 0.28 0.36 0.72 0.78 0.89 1.33 1.55 2.15
Transcribed Image Text:Species Mouse Bat Flying Fox Pigeon Guinea Pig Squirrel Chinchilla Rabbit Hare Cat Dog Macaque Sheep Bovine Human Body 58 30 130 500 485 350 500 1,800 3,000 3,500 3,500 6,000 25,000 300,000 60,000 Cerebellum Log (body) Log (cerebellum) 1.76 1.48 2.11 2.70 2.69 2.54 2.70 3.26 3.48 3.54 3.54 3.78 4.40 5.48 4.78 0.09 0.09 0.30 0.40 0.90 1.50 1.70 1.90 2.30 5.30 6.00 7.80 21.50 35.70 142.00 -1.05 -1.05 -0.52 -0.40 -0.05 0.18 0.23 0.28 0.36 0.72 0.78 0.89 1.33 1.55 2.15
Expert Solution
Introduction

You can use a statistical technique called simple linear regression to comprehend the 

relationship between two variables, x and y.

where X is predictor variable

Y is response variable.

The formula for the line of best fit is written as:

ŷ = b0 + b1x

 

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