DSE Exploratory Data Analysis Techniques 3

Question 1

Which plot is most appropriate for visualizing the joint distribution of two continuous variables along with their marginal distributions?

Accepted Answer

Joint plot (with marginal histograms)

Answer

A joint plot displays a scatter or density plot in the center with marginal histograms or KDE curves along each axis, showing both joint and individual distributions.

Question 2

You notice that a numeric column has values ranging from 1 to 1,000,000 with most values under 1,000. Which transformation would best reveal structure in the lower range?

Accepted Answer

Logarithmic transformation

Answer

A log transformation compresses large values while expanding small values, making structure in the dense lower range visible without losing the high-end variation.

Question 3

What does a high kurtosis value (leptokurtic distribution) indicate about a dataset?

Accepted Answer

The distribution has heavy tails and a sharp peak

Answer

Leptokurtic distributions have excess kurtosis greater than 0, indicating heavier tails and more frequent extreme values than a normal distribution.

Question 4

Which EDA technique would you use to detect multicollinearity among predictor variables before modeling?

Accepted Answer

Correlation matrix or variance inflation factors

Answer

A correlation matrix reveals linear dependencies between predictors, and VIF quantifies how much one predictor's variance is explained by others.

Question 5

In EDA, what is a 'rug plot'?

Accepted Answer

Tick marks along an axis showing individual data point locations

Answer

A rug plot places short vertical tick marks along an axis at each data point's position, showing the actual distribution of individual observations.

DSE - Data Science Practice Test

DSE - Data Science Practice Test

DSE Exploratory Data Analysis Techniques 3