**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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