
Exploring Data Representation and Outliers

Quiz
•
Computers
•
University
•
Easy
kanipriya M
Used 2+ times
FREE Resource
15 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What are the main types of data representation in data mining?
Graph data
Structured data, unstructured data, semi-structured data, time-series data.
Spatial data
Categorical data
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does structured data differ from unstructured data?
Structured data is organized and easily searchable, while unstructured data is unorganized and harder to analyze.
Structured data is always in text format, while unstructured data is in numerical format.
Structured data can only be stored in databases, whereas unstructured data can only be stored in files.
Unstructured data is organized and easily searchable, while structured data is unorganized and harder to analyze.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of data normalization in data representation?
To increase data redundancy and decrease data integrity.
To enhance data visualization and presentation.
To simplify data storage without affecting data quality.
The purpose of data normalization is to reduce data redundancy and improve data integrity.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Name two common methods for outlier detection.
Median method
Z-score method, IQR method
Mean method
Standard deviation method
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the Z-score method used for in outlier analysis?
To visualize data distribution using histograms.
To identify outliers by measuring how far data points deviate from the mean.
To calculate the mean of the dataset.
To determine the median of the data points.
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What role does clustering play in outlier detection?
Clustering is used to increase the number of data points in a dataset.
Clustering has no impact on the identification of outliers.
Clustering eliminates outliers by merging them with nearby points.
Clustering helps identify outliers by grouping similar data points and highlighting those that do not fit well within any cluster.
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How can statistical tests be used to identify outliers?
Statistical tests can only confirm data accuracy.
Outliers are always removed from datasets automatically.
Statistical tests are not applicable to small sample sizes.
Statistical tests like z-scores and IQR can identify outliers.
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