Review the article Beware Spurious Correlations posted in this module readings. According to the article, which of
Question:
Review the article “Beware Spurious Correlations” posted in this module readings. According to the article, which of the examples below may lead to a spurious correlation?
Comparing dissimilar variables
Manipulating the ranges to align data
Plotting unrelated data sets together
All of the above
5 points
QUESTION 2
Review the article “Correlations in Finance” by Investopedia posted in this module readings. According to the article, if the stock is moving in the same direction as a benchmark index such as S&P 500, then
no correlation exists between the stock and the index
there is a positive correlation between the stock and the index
there is a negative correlation between the stock and the index
None of the above
5 points
QUESTION 3
What is a statistical measure that is used to analyze the strength of relationships between attributes in the dataset?
R-Squared
p-value
correlation
alpha score
5 points
QUESTION 4
Assume that the correlation between humidity and cement strength is -0.5959 and statistically significant. How can we interpret this result?
The more humidity the weaker the cement
The more humidity the stronger the cement
There is no effect of humidity on cement strength
Humidity and cement strength are not correlated
5 points
QUESTION 5
Assume that the correlation between sleep and level of oxygen is 0.8622 and statistically significant. How can we interpret this result?
The more sleep the higher the level of oxygen
The more sleep the lower the level of oxygen
There is no effect of sleep on the level of oxygen
Sleep and oxygen are not correlated
5 points
QUESTION 6
What is the task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups?
Itemset analysis
Cluster analysis
Network analysis
Social network analysis
5 points
QUESTION 7
Cluster analysis is
an unsupervised technique
a supervised technique
a semi-supervised technique
a reinforced learning technique
5 points
QUESTION 8
Which cluster solution is appropriate for nominal (categorical) data?
Hierarchical clustering
K-means clustering
Dendrogram
Complete linkage
5 points
QUESTION 9
In RapidMiner, which operator select the optimal number of clusters based on data?
K-means
Divisive
Agglomeration
X-means
5 points
QUESTION 10
When the distance between two clusters is defined as the distance between the nearest pair of objects with each object in the pair belonging to a distinct cluster, it is called
Nearest neighbor linkage
Complete linkage
Farthest neighbor linkage
Average linkage
5 points
QUESTION 11
Questions 11-15 are based on the “Chapter 4 Exercise” dataset. Upload Chapter04Exercise data to RapidMiner, and answer the following questions:
Upload the file, run the model, and explore the results. How many attributes are in the dataset?3
4
5
7
5 points
QUESTION 12
Add the operator Correlation Matrix, connect the ports, and run the model. Examine the correlation matrix.
Is the following statement true: attributes Vehicle Weight (Vweight) and Engine Size (Engine_Size) are highly positively correlated?True
False
5 points
QUESTION 13
Continue examining the correlation matrix. Is the following assumption true: the larger the engine size the greater the number of cylinders.
True
False
5 points
QUESTION 14
Continue examining the correlation matrix. Is the following assumption true: the larger the engine size the smaller the horse power.
True
False
5 points
QUESTION 15
Continue examining the correlation matrix. Is the following assumption true: the smaller the vehicle weight, the smaller MPG.
True
False
5 points
QUESTION 16
Questions 16-20 are based on the “Chapter 6 Exercise” dataset.
Upload Chapter06Exercise data to RapidMiner. Use operator Select Attributes to remove categorical variables First Name
and Last Name from the analysis. Then use operator Set Role to set the target role ‘id’ to the attribute Student_ID How many regular attributes are now in the dataset?7
8
9
10
5 points
QUESTION 17
Add the operator K-Means. In the parameters, change the number of k to 3, and have ‘add as label’ checked. Run the model and check the stats. What is the size of the largest cluster?
266
365
621
468
5 points
QUESTION 18
Add the operator Cluster Model Visualizer. Run the results. Explore the Overview section of the ClusterModelVisualizer results. Which cluster has the lowest number of absences?
The largest cluster
The smallest cluster
The middle cluster
There is no difference between clusters
5 points
QUESTION 19
Replace the operator K-Means with operator K-Means(fast). Keep all other operators. In the parameters of K-Means(fast) change the number of k to 3 and have ‘add as label’ checked. Run the model and check the stats. What is the size of the largest cluster?
266
365
621
468
5 points
QUESTION 20
In the Design View, change the parameters of K-Means(fast). Change the ‘numerical measure’ to ‘ManhattanDistance’. Run the model and check the stats. What is the size of the largest cluster?
266
365
621
468
Auditing and Assurance services an integrated approach
ISBN: 978-0132575959
14th Edition
Authors: Alvin a. arens, Randal j. elder, Mark s. Beasley