Data Analytics using Python Visualizations - Creating Error Bars

What is the primary purpose of using error bars in data visualization?

• To highlight the mean value of data

• To show the variability or uncertainty in data

• To display the maximum and minimum values

• To indicate the trend of data over time

How are the X-axis values generated for plotting error bars in the example?

• Using 30 equally spaced numbers between 1 to 10

• Using a fixed range of numbers

• Using a logarithmic scale

• Using random numbers

What mathematical function is used to calculate the Y-axis values in the example?

• X^2 + 5

• 5 * X + 5

• 5 * X^3 + 5

• 5 * X^2 + 5

What is the role of random numbers in creating error bars?

• To set the color of the error bars

• To calculate the mean value

• To represent the variability range

• To determine the X-axis values

Which function is used to draw error bars in Matplotlib?

• scatter()

• plot()

• errorbar()

• bar()

What color is used for the error bars in the example?

• Red

• Blue

• Green

• Black

What does the 'O' parameter specify in the error bar plot?

• The thickness of the error bars

• The shape of the data points

• The size of the error bars

• The color of the error bars