Which of the following statements about normal distribution is true?

The statement that normal distribution represents a symmetrical distribution of data is accurate because a normal distribution is characterized by its bell-shaped curve, where the left and right sides are mirror images of each other. This symmetry indicates that data points are evenly distributed around the mean, with most values clustering around the center and exponentially fewer values appearing as you move further away from the mean in either direction.

In a normal distribution, the mean, median, and mode all coincide at the central peak of the curve, reinforcing the concept of symmetry. This property is crucial in various fields such as statistics and engineering, as it allows for predictable patterns in data analysis and makes it easier to apply statistical methods that assume normality.

In contrast, the other statements are misleading: a normal distribution does not resemble a rectangle, it is not skewed (as it is perfectly symmetrical), and it certainly has a distinct central peak. Understanding the characteristics of normal distribution is foundational in engineering and design, especially when analyzing data sets and making predictions based on statistical models.