DSE - Data Science Exploratory Data Analysis Techniques Questions and Answers

Question 1

A data scientist is beginning to work with a new dataset of customer transactions. Which of the following is the PRIMARY goal of Exploratory Data Analysis (EDA) in this initial phase?

Accepted Answer

To summarize the main characteristics of the data and uncover initial patterns.

Answer

To build a predictive machine learning model with high accuracy.

Answer

To formally test predefined hypotheses about customer behavior.

Answer

To deploy the data into a production database for real-time analysis.

Question 2

During the EDA process for a housing price dataset, you create a scatter plot of 'square footage' versus 'price' and observe a strong positive linear relationship. This is an example of which type of EDA technique?

Accepted Answer

Multivariate graphical

Answer

Univariate non-graphical

Answer

Univariate graphical

Answer

Multivariate non-graphical

Question 3

A data analyst is using a box plot to examine the distribution of salaries for a specific job role. The plot reveals several data points located far beyond the whiskers of the box. What is the most likely interpretation of these points?

Accepted Answer

Potential outliers

Answer

The median salary

Answer

The interquartile range (IQR)

Answer

Missing data values

Question 4

Which of the following techniques is most suitable for understanding the relationships between multiple continuous variables simultaneously during EDA?

Accepted Answer

Correlation matrix with a heatmap

Answer

Histogram

Answer

Bar chart

Answer

Pie chart

Question 5

A data science team is analyzing a dataset with many features (high dimensionality). To simplify the data and aid in visualization, they apply a technique that reduces the number of variables while retaining most of the original information. Which EDA technique are they most likely using?

Accepted Answer

Principal Component Analysis (PCA)

Answer

Outlier detection

Answer

Hypothesis testing

Answer

Data profiling

Question 6

What is a key difference between Exploratory Data Analysis (EDA) and Confirmatory Data Analysis (CDA), such as formal hypothesis testing?

Accepted Answer

EDA is an open-ended process of generating hypotheses, while CDA aims to rigorously test pre-specified hypotheses.

Answer

EDA uses graphical techniques, while CDA exclusively uses statistical calculations.

Answer

EDA is only performed on small datasets, while CDA is used for big data.

Answer

EDA focuses on data cleaning, while CDA focuses on model building.

A data scientist is beginning to work with a new dataset of customer transactions.Which of the following is the PRIMARY goal of Exploratory Data Analysis (EDA) in this initial phase?

A data scientist is beginning to work with a new dataset of customer transactions.
Which of the following is the PRIMARY goal of Exploratory Data Analysis (EDA) in this initial phase?