Here are the essential concepts you must grasp in order to answer the question correctly.
Normal Distribution
The normal distribution is a continuous probability distribution characterized by its bell-shaped curve, symmetric about the mean. It is defined by two parameters: the mean (average) and the standard deviation (spread). In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean, 95% within two, and 99.7% within three, making it essential for statistical analysis.
Recommended video:
Using the Normal Distribution to Approximate Binomial Probabilities
Mean
The mean is the average value of a set of numbers, calculated by summing all values and dividing by the count of values. In the context of a normal distribution, the mean represents the center of the distribution, where the highest point of the curve occurs. It is a measure of central tendency that provides a useful summary of the data set.
Recommended video:
Standard Deviation
Standard deviation is a statistic that quantifies the amount of variation or dispersion in a set of values. A low standard deviation indicates that the values tend to be close to the mean, while a high standard deviation indicates a wider spread. In the context of the normal distribution, it helps determine the width of the curve and the proportion of data within specific ranges around the mean.
Recommended video:
Calculating Standard Deviation