Q1: [Regression and Correlation] The index of biotic integrity (IBI) is a measure of water quality in streams. As a data analyst you must monitor, track, and predict changes in water quality. You want to create a simple linear regression model that will allow you to predict changes in IBI in forested area. The following table conveys sample data from a coastal forest region and gives the data for IBI and forested area in square kilometers. Let forest area be the predictor variable (x) and IBI be the response variable (y). IBI X 47 72 21 19 72 58 49 Forest Area Y 38 59 27 24 63 49 45 Required a. b. c. Compute the error coefficient Plot Scatter graph Determine the regression equation d. Compute the correlation coefficient of the given data e. Estimate the forest area if IBI is 300
Q1: [Regression and Correlation] The index of biotic integrity (IBI) is a measure of water quality in streams. As a data analyst you must monitor, track, and predict changes in water quality. You want to create a simple linear regression model that will allow you to predict changes in IBI in forested area. The following table conveys sample data from a coastal forest region and gives the data for IBI and forested area in square kilometers. Let forest area be the predictor variable (x) and IBI be the response variable (y). IBI X 47 72 21 19 72 58 49 Forest Area Y 38 59 27 24 63 49 45 Required a. b. c. Compute the error coefficient Plot Scatter graph Determine the regression equation d. Compute the correlation coefficient of the given data e. Estimate the forest area if IBI is 300
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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Question
![Q1: [Regression and Correlation]
The index of biotic integrity (IBI) is a measure of water quality in streams. As a data analyst you must monitor, track, and predict changes
in water quality. You want to create a simple linear regression model that will allow you to predict changes in IBI in forested area. The
following table conveys sample data from a coastal forest region and gives the data for IBI and forested area in square kilometers. Let
forest area be the predictor variable (x) and IBI be the response variable (y).
IBI
X
47
72
21
72234
19
58
49
Forest Area
Y
38
59
27
24
63
49
45
Required
a.
Q2: [Naïve Bayes]
a. Write the pseudo-code of the following Naïve Bayes algorithm
b. Consider the given dataset that classifies animals into two distinct classes. The classes are labeled as 'cat' and
'dog'. Use Naive Bayes classifier to figure out the class (cat/dog) of an instance if it has the following values of
attributed
Plot Scatter graph
b. Determine the regression equation
c. Compute the error coefficient
d. Compute the correlation coefficient of the given data
e. Estimate the forest area if IBI is 300
Hair-black, Body Length-20, Height = 10, Weight=9, Ear length=2, Claws = TRUE
hair color body length (in) height (in) weight (lb) ear length (in)
class
black
18
9.2
8.1
2
20.1
17
15.5
grey
orange
brown
white
black
1
2
17
23.5
16
21
3
4
9.1
20
9.0
16.7
6
3
3
Q3 [K-Nearest Neighbor]
The quality of tissue paper is the measure of acid durability and tissue paper strength. In this connection a tissue paper company has
conducted a survey from random sample about Good Feel or Bad Feel of tissue paper. Further, the corresponding acid durability and
strength are measured of respective tissue paper. The data is illustrated in the following table. As the test sample the factory produces a
new paper tissue that passes laboratory tests with Acid Durability (sec)-4 and Strength (Kg/m²)-8. Given that K-3, Use the KNN
algorithm to find the output class of the test sample
Id
9
Acid Durability Strength
(sec)
(Kg/m²)
X1
X2
6
7
4
5
20
10
16
5
claws
TRUE
cat
FALSE dog
cat
1.95
TRUE
6.2 FALSE dog
2.1
TRUE cat
3.3 FALSE dog
5
Output Class
(Y)
Bad
Bad
Good
Good](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F37584fce-d85b-4e67-9c6c-d1b0394044cd%2Fec4db4d8-bac3-4618-89a2-55fc71aceec9%2F851589_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Q1: [Regression and Correlation]
The index of biotic integrity (IBI) is a measure of water quality in streams. As a data analyst you must monitor, track, and predict changes
in water quality. You want to create a simple linear regression model that will allow you to predict changes in IBI in forested area. The
following table conveys sample data from a coastal forest region and gives the data for IBI and forested area in square kilometers. Let
forest area be the predictor variable (x) and IBI be the response variable (y).
IBI
X
47
72
21
72234
19
58
49
Forest Area
Y
38
59
27
24
63
49
45
Required
a.
Q2: [Naïve Bayes]
a. Write the pseudo-code of the following Naïve Bayes algorithm
b. Consider the given dataset that classifies animals into two distinct classes. The classes are labeled as 'cat' and
'dog'. Use Naive Bayes classifier to figure out the class (cat/dog) of an instance if it has the following values of
attributed
Plot Scatter graph
b. Determine the regression equation
c. Compute the error coefficient
d. Compute the correlation coefficient of the given data
e. Estimate the forest area if IBI is 300
Hair-black, Body Length-20, Height = 10, Weight=9, Ear length=2, Claws = TRUE
hair color body length (in) height (in) weight (lb) ear length (in)
class
black
18
9.2
8.1
2
20.1
17
15.5
grey
orange
brown
white
black
1
2
17
23.5
16
21
3
4
9.1
20
9.0
16.7
6
3
3
Q3 [K-Nearest Neighbor]
The quality of tissue paper is the measure of acid durability and tissue paper strength. In this connection a tissue paper company has
conducted a survey from random sample about Good Feel or Bad Feel of tissue paper. Further, the corresponding acid durability and
strength are measured of respective tissue paper. The data is illustrated in the following table. As the test sample the factory produces a
new paper tissue that passes laboratory tests with Acid Durability (sec)-4 and Strength (Kg/m²)-8. Given that K-3, Use the KNN
algorithm to find the output class of the test sample
Id
9
Acid Durability Strength
(sec)
(Kg/m²)
X1
X2
6
7
4
5
20
10
16
5
claws
TRUE
cat
FALSE dog
cat
1.95
TRUE
6.2 FALSE dog
2.1
TRUE cat
3.3 FALSE dog
5
Output Class
(Y)
Bad
Bad
Good
Good
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