What shape characterizes a normal distribution?

What shape characterizes a normal distribution?

• A. A skewed distribution.
• B. A flat histogram.
• C. A discrete distribution.
• D. A symmetrical bell-shaped graph.

Answer: (D)

A normal distribution is defined by a symmetrical bell-shaped curve centered at the mean. This shape shows that most data cluster around the average, with probabilities tapering smoothly in both directions as values become more extreme. It is a continuous distribution, so the graph is a smooth curve rather than discrete bars. The symmetry means the left and right sides mirror each other, making extreme values similarly unlikely on either side. Other options describe shapes that don’t match this pattern: a skewed shape is asymmetrical, a flat histogram suggests a uniform distribution, and a discrete distribution refers to individual values rather than a continuous bell curve.

A normal distribution is defined by a symmetrical bell-shaped curve centered at the mean. This shape shows that most data cluster around the average, with probabilities tapering smoothly in both directions as values become more extreme. It is a continuous distribution, so the graph is a smooth curve rather than discrete bars. The symmetry means the left and right sides mirror each other, making extreme values similarly unlikely on either side. Other options describe shapes that don’t match this pattern: a skewed shape is asymmetrical, a flat histogram suggests a uniform distribution, and a discrete distribution refers to individual values rather than a continuous bell curve.