Which term describes the overall shape of a distribution in terms of height and width (platykurtic, normal, leptokurtic)?

Which term describes the overall shape of a distribution in terms of height and width (platykurtic, normal, leptokurtic)?

• A. Kurtosis
• B. Skewness
• C. Variance
• D. Range

Answer: (A)

Kurtosis describes how tall or flat the peak of a distribution is and how thick the tails are. If a distribution is leptokurtic, the peak is tall and the tails are heavy; if it’s platykurtic, the peak is flatter with thinner tails; a normal distribution has a typical, moderate peak often called mesokurtic. Skewness would tell you about asymmetry between the left and right sides, not height/width. Variance measures how spread out values are around the mean, and range is simply the gap between the smallest and largest values. So, the term that best captures the overall shape in terms of height and width is kurtosis.

Kurtosis describes how tall or flat the peak of a distribution is and how thick the tails are. If a distribution is leptokurtic, the peak is tall and the tails are heavy; if it’s platykurtic, the peak is flatter with thinner tails; a normal distribution has a typical, moderate peak often called mesokurtic. Skewness would tell you about asymmetry between the left and right sides, not height/width. Variance measures how spread out values are around the mean, and range is simply the gap between the smallest and largest values. So, the term that best captures the overall shape in terms of height and width is kurtosis.