DSE DSE - Data Science Data Visualization and Communication 1 — Questions and Answers
Question 1: Which Python library is most commonly used for creating static statistical visualizations in data science?
- Plotly
- Matplotlib (Correct answer)
- Bokeh
- Altair
Correct answer: Matplotlib
Matplotlib is the foundational Python plotting library widely used for static statistical charts and visualizations in data science.
Question 2: What type of chart is best suited for showing the frequency distribution of a single continuous variable?
- Bar chart
- Scatter plot
- Histogram (Correct answer)
- Line chart
Correct answer: Histogram
A histogram divides continuous data into bins and displays their frequencies, making it ideal for showing the distribution of a single continuous variable.
Question 3: Which visualization technique best shows the correlation between two continuous variables?
- Pie chart
- Scatter plot (Correct answer)
- Stacked bar chart
- Box plot
Correct answer: Scatter plot
A scatter plot places each observation as a point on a 2D plane using two continuous axes, making correlation patterns visually apparent.
Question 4: In a box plot, what do the 'whiskers' typically represent?
- Standard deviation
- Mean ± 1 standard error
- 1.5× the interquartile range from Q1 and Q3 (Correct answer)
- Minimum and maximum values only
Correct answer: 1.5× the interquartile range from Q1 and Q3
By default, box plot whiskers extend to 1.5 times the IQR beyond Q1 and Q3, with points beyond that considered outliers.
Question 5: Which chart type is most appropriate for comparing proportions that sum to a whole?
- Scatter plot
- Histogram
- Pie chart (Correct answer)
- Heatmap
Correct answer: Pie chart
A pie chart divides a circle into slices proportional to each category's share of the total, making part-to-whole comparisons intuitive.
Question 6: What is the primary analytical purpose of a heatmap in data science?
- Showing time-series trends
- Visualizing magnitude across a two-dimensional matrix using color intensity (Correct answer)
- Displaying hierarchical relationships
- Comparing distributions across groups
Correct answer: Visualizing magnitude across a two-dimensional matrix using color intensity
A heatmap encodes numeric values in a grid as colors, making it easy to spot patterns, clusters, or anomalies across two categorical dimensions.
DSE DSE - Data Science Data Visualization and Communication 1
Which Python library is most commonly used for creating static statistical visualizations in data science?