Data Science Final Exam Questions
with 100% Verified Answers
Which of the following are fields that contribute to Data Mining - ✔ ✔ Algorithms
Machine Learning and Statistics
Visualization
Hardware development (for fast computation)
Databases
When using the classification data mining functionality, the goal is to
- ✔ ✔ determine a correct class label for a new input data instance.
Select the pieces of advice that were provided for people new to using data
mining. - ✔ ✔ -Understand the needs of the end user (along with the
problem domain).
-Data preparation (cleaning and pre-processing) can be up to 80% of the time
spent.
-The only way to be sure if a technique works well is to try it with your data.
-Remember that business or scientific need is a higher priority than
technical excitement.
Text data can be stored in a matrix with a "bag-of-words" model. This means: -
✔ ✔ each row represents a unit of text (e.g. document) and each column
represents a word.
, Which of the following is true about data cubes. - ✔ ✔ -They are a a
representation of high-dimensional data.
-They support hierarchical operations like aggregation, or "roll-up" and "drill-
down"
The reason to carefully use data cleaning and pre-processing is summed up
by, "Garbage in, Garbage out." - ✔ ✔ True
Select all of the following that are true about Data Warehouses - ✔ ✔ -Data
will not be modified by the end user.
-Data may be integrated and cleaned from many large sources.
A classifier is used to - ✔ ✔ discover a pattern that can predict a class that a
new data instance falls into.
As opposed to supervised learning, unsupervised learning - ✔ ✔ -
includes clustering
-find groups in data without provided labels
Binning numerical data into chunks (bins) can be useful for - ✔ ✔ -dealing with
noisy data by smoothing out lots of variation into chunks with reasonable ranges
-drawing a histogram
Which of the following is true about data normalization? - ✔ ✔ -Normalization
scales the range of the data into some (generally smaller) specified range.
-Z-Score normalization is useful for finding outliers because each point is
represented by how far from the mean it is
with 100% Verified Answers
Which of the following are fields that contribute to Data Mining - ✔ ✔ Algorithms
Machine Learning and Statistics
Visualization
Hardware development (for fast computation)
Databases
When using the classification data mining functionality, the goal is to
- ✔ ✔ determine a correct class label for a new input data instance.
Select the pieces of advice that were provided for people new to using data
mining. - ✔ ✔ -Understand the needs of the end user (along with the
problem domain).
-Data preparation (cleaning and pre-processing) can be up to 80% of the time
spent.
-The only way to be sure if a technique works well is to try it with your data.
-Remember that business or scientific need is a higher priority than
technical excitement.
Text data can be stored in a matrix with a "bag-of-words" model. This means: -
✔ ✔ each row represents a unit of text (e.g. document) and each column
represents a word.
, Which of the following is true about data cubes. - ✔ ✔ -They are a a
representation of high-dimensional data.
-They support hierarchical operations like aggregation, or "roll-up" and "drill-
down"
The reason to carefully use data cleaning and pre-processing is summed up
by, "Garbage in, Garbage out." - ✔ ✔ True
Select all of the following that are true about Data Warehouses - ✔ ✔ -Data
will not be modified by the end user.
-Data may be integrated and cleaned from many large sources.
A classifier is used to - ✔ ✔ discover a pattern that can predict a class that a
new data instance falls into.
As opposed to supervised learning, unsupervised learning - ✔ ✔ -
includes clustering
-find groups in data without provided labels
Binning numerical data into chunks (bins) can be useful for - ✔ ✔ -dealing with
noisy data by smoothing out lots of variation into chunks with reasonable ranges
-drawing a histogram
Which of the following is true about data normalization? - ✔ ✔ -Normalization
scales the range of the data into some (generally smaller) specified range.
-Z-Score normalization is useful for finding outliers because each point is
represented by how far from the mean it is
