Data mining and warehousing mcq
1. Which of the following applied on warehouse?
- write only
- read only
- both
- a & b none
read only
2. Data can be store , retrive and updated in
- SMTOP
- OLTP
- FTP
- OLAP
OLTP
3. Data mining is Extraction of interesting (non-trivial, implicit, previously unknown and potentially useful) information or patterns from data in large databases
- TRUE
- FALSE
TRUE
4. Data in the real world is
- incomplete
- inconsitent
- noisy
- all of above
all of above
5. What are Measure of Data Quality
- Accuracy
- Completeness
- Consistency
- all
all
6. Data cleaning is fill in missing values, smooth noisy data, identify or remove outliers, and resolve inconsistencies
- TRUE
- FALSE
TRUE
7. Data integration is Integration of multiple databases, data cubes, or files
- TRUE
- FALSE
TRUE
8. Data transformation is Normalization and aggregation
- TRUE
- FALSE
TRUE
9. Data reduction Obtains reduced representation in volume but produces the same or similar analytical results
- TRUE
- FALSE
TRUE
10. Data discretization is Part of data reduction but with particular importance, especially for numerical data
- TRUE
- FALSE
TRUE
Data mining and warehousing mcq sppu
11. Missing data may be due to
- equipment malfunction
- inconsistent with other recorded data and thus deleted data not entered due to misunderstanding
- certain data may not be considered important at the time of entry
- all
all
12. Incorrect attribute values may due to
- faulty data collection instruments
- data entry problems
- data transmission problems
- all
all
13. data cleaning is not required for duplicate records
- TRUE
- FALSE
FALSE
14. Binning method first sort data and partition into (equi-depth) bins
- TRUE
- FALSE
TRUE
15. Data can be smoothed by fitting the data to a function, such as with regression.
- TRUE
- FALSE
TRUE
16. Linear regression – involves finding the________ line to fit two attributes (or variables)
- best
- average
- worst
best
17. Data cleaning is fill in __ values
- existing
- missing
missing
18. Data transformation is ________________and aggregation
- Normalization
- Denormalization
Normalization
19. Data reduction Obtains reduced representation in volume but produces the_________ or similar analytical results
- same
- different
same
data mining and warehousing mcq sppu
20. Data discretization is Part of data reduction but with particular importance, especially for _____________data
- Character
- numerical
numerical
21. Redundant data occur often when integration of multiple databases
- TRUE
- FALSE
TRUE
22. The same attribute may have different names in different databases
- TRUE
- FALSE
TRUE
23. Careful integration of the data from multiple sources may help reduce/avoid redundancies and inconsistencies
- TRUE
- FALSE
TRUE
24. Correlation coefficient is also called Pearson’s product moment coefficient
- TRUE
- FALSE
TRUE
25. Min-max normalization performs a linear transformation on the original data.
- TRUE
- FALSE
TRUE
26. The values for an attribute, A, are normalized based on the mean and standard deviation of A
- Min-max normalization
- z-score normalization
z-score normalization
27. The values for an attribute, A, are normalized based on the mean and standard deviation of A in z-score normalization
- TRUE
- FALSE
TRUE
28. z-score normalization is useful when the actual minimum and maximum of attribute A are unknown
- TRUE
- FALSE
TRUE
29. Normalization by decimal scaling normalizes by moving the decimal point of values of attribute A.
- TRUE
- FALSE
TRUE
30. Data reduction obtains a reduced representation of the data set that is much smaller in volume but yet produces the same (or almost the same) analytical results
- TRUE
- FALSE
TRUE
data mining and warehousing mcq questions
31. Run Length Encoding is lossless
- TRUE
- FALSE
TRUE
32. Jpeg compression is
- lossy
- lossless
lossy
33. Wavelet Transform Decomposes a signal into different frequency subbands
- TRUE
- FALSE
TRUE
34. Principal Component Analysis (PCA) is used for dimensionality reduction
- TRUE
- FALSE
TRUE
35. Normalization by______________ scaling normalizes by moving the decimal point of values of attribute A
- binary
- octal
- decimal
decimal
36. Data cube aggregation is normalization
- TRUE
- FALSE
TRUE
37. ordinal attribute have values from an ___________set
- ordered
- unordered
ordered
38. Nominal attribute have values from an ___________set
- TRUE
- FALSE
FALSE
39. Run Length Encoding is
- lossy
- lossless
lossless
Data Analytics sppu mcq
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