30 Questions
What does 'incomplete' data refer to?
Data with missing attribute values or lacking certain attributes
Which is an example of 'noisy' data?
Salary=“−10” (an error)
In data cleaning, what is one reason for missing data?
Equipment malfunction
How is missing data usually handled when the class label is missing?
Ignore the tuple
What is a suggested method for filling in missing values automatically?
Use a global constant to fill in the missing value
Why might certain data not be considered important at the time of entry?
Due to misunderstanding
What does the null rule specify?
Handling blanks, question marks, special characters, or other indicative strings for null condition
What is ETL in the context of data migration and integration?
Extraction/Transformation/Loading
Which major task is NOT part of Data Preprocessing?
Data Visualization
What is the purpose of data scrubbing in data cleaning?
Detecting errors using simple domain knowledge and making corrections
What is the primary goal of data integration?
Combining data from multiple sources into a coherent store
What does entity identification problem refer to in data integration?
Identifying real-world entities from multiple data sources
What is a possible reason for attribute values from different sources to be different?
Different representations
In data integration, what is one way to detect redundant attributes?
Correlation analysis
What does a larger Χ2 value indicate in correlation analysis of nominal data?
Variables are more likely related
In the Chi-Square calculation example provided, how is the Chi-Square value calculated?
Sum of squared differences between observed and expected counts
What does the Correlation Coefficient measure in correlation analysis of numeric data?
The linear relationship between variables
What does it mean when two attributes have a high Correlation Coefficient value?
They have a strong linear relationship
What is the purpose of splitting in the context of unsupervised data preprocessing?
To recursively prepare data for further analysis like classification
What is a common technique mentioned for data smoothing in the text?
Calculating bin means
What is the purpose of concept hierarchy generation in a data warehouse?
To view data at multiple granularity levels
How are concept hierarchies usually formed according to the text?
By recursively reducing data and replacing low level concepts with higher level ones
Which task is NOT a part of data preprocessing based on the text?
Data partitioning into equal-frequency bins
What does data transformation and discretization involve according to the text?
Replacing low level concepts with higher level ones
What does a positive covariance between two variables indicate?
Both variables tend to be larger than their expected values
What does a covariance of 0 between two variables suggest?
The variables are independent
How does negative covariance impact the relationship between two variables?
If one variable is larger than its expected value, the other is likely smaller
When does a covariance of 0 imply independence between two variables?
Only when the data follow multivariate normal distributions
In the context of stock prices, what does it mean when two stocks have a positive covariance?
Their prices will rise together
What is the relationship between correlation coefficient and covariance?
Correlation coefficient measures strength and direction, while covariance measures direction only
Learn about the process of detecting and resolving data value conflicts in data integration, where attribute values from different sources vary due to reasons such as different representations or scales. Explore the challenges of handling redundancy in data integration, including issues with object identification and derivable data.
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