Data Science Multiple Choice Questions on “ToolBox Overview”.
1. Standard normal RVs are always labelled as Z.
a) True
b) False
Answer: b
Explanation: Standard normal RVs are often labelled as Z.
2. Point out the correct statement.
a) Least square is an estimation tool
b) Least square problems falls in to three categories
c) Compound least square is one of the category of least square
d) None of the mentioned
Answer: a
Explanation: The Method of Least Squares is a procedure to determine the best fit line to data.
3. How many principles of analytical graphs exist?
a) 3
b) 4
c) 6
d) None of the mentioned
Answer: c
Explanation: Six Principles of Analytical Graphs are useful for data analysis.
4. Which of the following is not a step in data analysis?
a) Obtain the data
b) Clean the data
c) EDA
d) None of the mentioned
Answer: d
Explanation: EDA stands for Exploratory Data Analysis.
5. Point out the wrong statement.
a) Simple linear regression is equipped to handle more than one predictor
b) Compound linear regression is not equipped to handle more than one predictor
c) Linear regression consists of finding the best-fitting straight line through the points
d) All of the mentioned
Answer: a
Explanation: Simple linear regression is equipped to handle more than one predictor.
6. Which of the following technique comes under practical machine learning?
a) Bagging
b) Boosting
c) Forecasting
d) None of the mentioned
Answer: b
Explanation: Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor.
7. Which of the following technique is also referred to as Bagging?
a) Bootstrap aggregating
b) Bootstrap subsetting
c) Bootstrap predicting
d) All of the mentioned
Answer: a
Explanation: Bagging is used in statistical classification and regression.
8. Which of the following is characteristic of Raw Data?
a) Data is ready for analysis
b) Original version of data
c) Easy to use for data analysis
d) None of the mentioned
Answer: b
Explanation: Raw data is data that has not been processed for use.