To make your own Normal quantile plot of the data in Group 3 for plots of forest that were logged 8 years earlier and first, sort and rank the data from smallest to largest, second, calculate z-scores for the adults and third, make a scatterplot of the number of trees per plot against their calculated z-scores.

Question

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Answer 1

Question

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Chapter 11, Problem 11.50E

(a)

To determine

To make your own Normal quantile plot of the data in Group 3 for plots of forest that were logged 8 years earlier and first, sort and rank the data from smallest to largest, second, calculate z-scores for the adults and third, make a scatterplot of the number of trees per plot against their calculated z-scores.

(a)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, firstly we will sort the data from smallest to largest by using excel. That is first we will select the data and click the sort and filter option and then select ascending order. Thus, the result will be as:

Group 3
4
12
12
15
18
18
19
22
22

Now we will use the R programming to construct the Normal quantile plot and scatterplot by using the codes as:

G=c(18,4,22,15,18,19,22,12,12)z=qnorm(((1:9)−0.5)/9)library(plotly)data=data.frame("No_of_trees"=G,"Normal_scores"=z)figg=plot_ly(data=data,x=~Normal_scores,y=~No_of_trees)figgplot(x=z, y=G,col="red",xlab="Normal_scores",ylab="No_of_trees",main="Normal Quantile Plot")qqnorm(data$No_of_trees,pch=1, frame=FALSE)qqline(data$No_of_trees,col="blue",lwd=2)

And the plots are as:

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 1

The above plot is Normal quantile plot which shows the Normality of the data and in this we can see that the points are approximately in a straight line and increasing.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 2

This is the scatterplot of the data which shows the increasing nature of the graph and it is also in a straight line.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 3

(b)

To determine

To examine your Normal quantile plot for deviations from Normality and explain your conclusions.

(b)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, from the scatterplot in the part (a), we can say that if Normal scores increases the number of trees will also increase. The points seem to fail about a straight line and the x-axis plots the theoretical quantiles. Those are the quantiles from the standard Normal distribution with mean zero and standard deviation one. And also all the points are very close to the line constructed in the plot and so the data shows Normality.

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Answer 2

Question

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Chapter 11, Problem 11.50E

(a)

To determine

To make your own Normal quantile plot of the data in Group 3 for plots of forest that were logged 8 years earlier and first, sort and rank the data from smallest to largest, second, calculate z-scores for the adults and third, make a scatterplot of the number of trees per plot against their calculated z-scores.

(a)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, firstly we will sort the data from smallest to largest by using excel. That is first we will select the data and click the sort and filter option and then select ascending order. Thus, the result will be as:

Group 3
4
12
12
15
18
18
19
22
22

Now we will use the R programming to construct the Normal quantile plot and scatterplot by using the codes as:

G=c(18,4,22,15,18,19,22,12,12)z=qnorm(((1:9)−0.5)/9)library(plotly)data=data.frame("No_of_trees"=G,"Normal_scores"=z)figg=plot_ly(data=data,x=~Normal_scores,y=~No_of_trees)figgplot(x=z, y=G,col="red",xlab="Normal_scores",ylab="No_of_trees",main="Normal Quantile Plot")qqnorm(data$No_of_trees,pch=1, frame=FALSE)qqline(data$No_of_trees,col="blue",lwd=2)

And the plots are as:

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 1

The above plot is Normal quantile plot which shows the Normality of the data and in this we can see that the points are approximately in a straight line and increasing.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 2

This is the scatterplot of the data which shows the increasing nature of the graph and it is also in a straight line.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 3

(b)

To determine

To examine your Normal quantile plot for deviations from Normality and explain your conclusions.

(b)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, from the scatterplot in the part (a), we can say that if Normal scores increases the number of trees will also increase. The points seem to fail about a straight line and the x-axis plots the theoretical quantiles. Those are the quantiles from the standard Normal distribution with mean zero and standard deviation one. And also all the points are very close to the line constructed in the plot and so the data shows Normality.

Want to see more full solutions like this?

Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!

Answer 3

Question

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Chapter 11, Problem 11.50E

(a)

To determine

To make your own Normal quantile plot of the data in Group 3 for plots of forest that were logged 8 years earlier and first, sort and rank the data from smallest to largest, second, calculate z-scores for the adults and third, make a scatterplot of the number of trees per plot against their calculated z-scores.

(a)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, firstly we will sort the data from smallest to largest by using excel. That is first we will select the data and click the sort and filter option and then select ascending order. Thus, the result will be as:

Group 3
4
12
12
15
18
18
19
22
22

Now we will use the R programming to construct the Normal quantile plot and scatterplot by using the codes as:

G=c(18,4,22,15,18,19,22,12,12)z=qnorm(((1:9)−0.5)/9)library(plotly)data=data.frame("No_of_trees"=G,"Normal_scores"=z)figg=plot_ly(data=data,x=~Normal_scores,y=~No_of_trees)figgplot(x=z, y=G,col="red",xlab="Normal_scores",ylab="No_of_trees",main="Normal Quantile Plot")qqnorm(data$No_of_trees,pch=1, frame=FALSE)qqline(data$No_of_trees,col="blue",lwd=2)

And the plots are as:

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 1

The above plot is Normal quantile plot which shows the Normality of the data and in this we can see that the points are approximately in a straight line and increasing.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 2

This is the scatterplot of the data which shows the increasing nature of the graph and it is also in a straight line.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 3

(b)

To determine

To examine your Normal quantile plot for deviations from Normality and explain your conclusions.

(b)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, from the scatterplot in the part (a), we can say that if Normal scores increases the number of trees will also increase. The points seem to fail about a straight line and the x-axis plots the theoretical quantiles. Those are the quantiles from the standard Normal distribution with mean zero and standard deviation one. And also all the points are very close to the line constructed in the plot and so the data shows Normality.

Want to see more full solutions like this?

Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!

Answer 4

Question

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Chapter 11, Problem 11.50E

(a)

To determine

To make your own Normal quantile plot of the data in Group 3 for plots of forest that were logged 8 years earlier and first, sort and rank the data from smallest to largest, second, calculate z-scores for the adults and third, make a scatterplot of the number of trees per plot against their calculated z-scores.

(a)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, firstly we will sort the data from smallest to largest by using excel. That is first we will select the data and click the sort and filter option and then select ascending order. Thus, the result will be as:

Group 3
4
12
12
15
18
18
19
22
22

Now we will use the R programming to construct the Normal quantile plot and scatterplot by using the codes as:

G=c(18,4,22,15,18,19,22,12,12)z=qnorm(((1:9)−0.5)/9)library(plotly)data=data.frame("No_of_trees"=G,"Normal_scores"=z)figg=plot_ly(data=data,x=~Normal_scores,y=~No_of_trees)figgplot(x=z, y=G,col="red",xlab="Normal_scores",ylab="No_of_trees",main="Normal Quantile Plot")qqnorm(data$No_of_trees,pch=1, frame=FALSE)qqline(data$No_of_trees,col="blue",lwd=2)

And the plots are as:

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 1

The above plot is Normal quantile plot which shows the Normality of the data and in this we can see that the points are approximately in a straight line and increasing.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 2

This is the scatterplot of the data which shows the increasing nature of the graph and it is also in a straight line.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 3

(b)

To determine

To examine your Normal quantile plot for deviations from Normality and explain your conclusions.

(b)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, from the scatterplot in the part (a), we can say that if Normal scores increases the number of trees will also increase. The points seem to fail about a straight line and the x-axis plots the theoretical quantiles. Those are the quantiles from the standard Normal distribution with mean zero and standard deviation one. And also all the points are very close to the line constructed in the plot and so the data shows Normality.

Want to see more full solutions like this?

Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!

Answer 5

Chapter 11, Problem 11.50E

(a)

To determine

To make your own Normal quantile plot of the data in Group 3 for plots of forest that were logged 8 years earlier and first, sort and rank the data from smallest to largest, second, calculate z-scores for the adults and third, make a scatterplot of the number of trees per plot against their calculated z-scores.

(a)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, firstly we will sort the data from smallest to largest by using excel. That is first we will select the data and click the sort and filter option and then select ascending order. Thus, the result will be as:

Group 3
4
12
12
15
18
18
19
22
22

Now we will use the R programming to construct the Normal quantile plot and scatterplot by using the codes as:

G=c(18,4,22,15,18,19,22,12,12)z=qnorm(((1:9)−0.5)/9)library(plotly)data=data.frame("No_of_trees"=G,"Normal_scores"=z)figg=plot_ly(data=data,x=~Normal_scores,y=~No_of_trees)figgplot(x=z, y=G,col="red",xlab="Normal_scores",ylab="No_of_trees",main="Normal Quantile Plot")qqnorm(data$No_of_trees,pch=1, frame=FALSE)qqline(data$No_of_trees,col="blue",lwd=2)

And the plots are as:

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 1

The above plot is Normal quantile plot which shows the Normality of the data and in this we can see that the points are approximately in a straight line and increasing.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 2

This is the scatterplot of the data which shows the increasing nature of the graph and it is also in a straight line.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 3

(b)

To determine

To examine your Normal quantile plot for deviations from Normality and explain your conclusions.

(b)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, from the scatterplot in the part (a), we can say that if Normal scores increases the number of trees will also increase. The points seem to fail about a straight line and the x-axis plots the theoretical quantiles. Those are the quantiles from the standard Normal distribution with mean zero and standard deviation one. And also all the points are very close to the line constructed in the plot and so the data shows Normality.

Answer 6

Chapter 11, Problem 11.50E

(a)

To determine

To make your own Normal quantile plot of the data in Group 3 for plots of forest that were logged 8 years earlier and first, sort and rank the data from smallest to largest, second, calculate z-scores for the adults and third, make a scatterplot of the number of trees per plot against their calculated z-scores.

(a)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, firstly we will sort the data from smallest to largest by using excel. That is first we will select the data and click the sort and filter option and then select ascending order. Thus, the result will be as:

Group 3
4
12
12
15
18
18
19
22
22

Now we will use the R programming to construct the Normal quantile plot and scatterplot by using the codes as:

G=c(18,4,22,15,18,19,22,12,12)z=qnorm(((1:9)−0.5)/9)library(plotly)data=data.frame("No_of_trees"=G,"Normal_scores"=z)figg=plot_ly(data=data,x=~Normal_scores,y=~No_of_trees)figgplot(x=z, y=G,col="red",xlab="Normal_scores",ylab="No_of_trees",main="Normal Quantile Plot")qqnorm(data$No_of_trees,pch=1, frame=FALSE)qqline(data$No_of_trees,col="blue",lwd=2)

And the plots are as:

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 1

The above plot is Normal quantile plot which shows the Normality of the data and in this we can see that the points are approximately in a straight line and increasing.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 2

This is the scatterplot of the data which shows the increasing nature of the graph and it is also in a straight line.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 3

Answer 7

Chapter 11, Problem 11.50E

(a)

To determine

To make your own Normal quantile plot of the data in Group 3 for plots of forest that were logged 8 years earlier and first, sort and rank the data from smallest to largest, second, calculate z-scores for the adults and third, make a scatterplot of the number of trees per plot against their calculated z-scores.

Answer 8

(a)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, firstly we will sort the data from smallest to largest by using excel. That is first we will select the data and click the sort and filter option and then select ascending order. Thus, the result will be as:

Group 3
4
12
12
15
18
18
19
22
22

Now we will use the R programming to construct the Normal quantile plot and scatterplot by using the codes as:

G=c(18,4,22,15,18,19,22,12,12)z=qnorm(((1:9)−0.5)/9)library(plotly)data=data.frame("No_of_trees"=G,"Normal_scores"=z)figg=plot_ly(data=data,x=~Normal_scores,y=~No_of_trees)figgplot(x=z, y=G,col="red",xlab="Normal_scores",ylab="No_of_trees",main="Normal Quantile Plot")qqnorm(data$No_of_trees,pch=1, frame=FALSE)qqline(data$No_of_trees,col="blue",lwd=2)

And the plots are as:

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 1

The above plot is Normal quantile plot which shows the Normality of the data and in this we can see that the points are approximately in a straight line and increasing.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 2

This is the scatterplot of the data which shows the increasing nature of the graph and it is also in a straight line.

Practice of Statistics in the Life Sciences, Chapter 11, Problem 11.50E , additional homework tip 3

Answer 9

(a)

Expert Solution

Answer 10

(a)

Expert Solution

Answer 11

Expert Solution

Answer 12

(b)

To determine

To examine your Normal quantile plot for deviations from Normality and explain your conclusions.

(b)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, from the scatterplot in the part (a), we can say that if Normal scores increases the number of trees will also increase. The points seem to fail about a straight line and the x-axis plots the theoretical quantiles. Those are the quantiles from the standard Normal distribution with mean zero and standard deviation one. And also all the points are very close to the line constructed in the plot and so the data shows Normality.

Answer 13

(b)

To determine

To examine your Normal quantile plot for deviations from Normality and explain your conclusions.

Answer 14

(b)

Expert Solution

Explanation of Solution

In the question, the data is given that described of the effects of logging on counts in the Borneo rainforest as:

Group 3
18
4
22
15
18
19
22
12
12

Thus, from the scatterplot in the part (a), we can say that if Normal scores increases the number of trees will also increase. The points seem to fail about a straight line and the x-axis plots the theoretical quantiles. Those are the quantiles from the standard Normal distribution with mean zero and standard deviation one. And also all the points are very close to the line constructed in the plot and so the data shows Normality.