Problemas
Ben Jones QDataRemixed - Jul 26 Stats Quiz: The average NFL player is about 25 years old, just over 6'2'' in height. weighs a little more than 244lbs and makes slightly less than 1.5M in salary per year. Can you tell which distribution goes with which trait? See why the shape of the distribution matters a lot? 32 17 154 B D
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Raúl
veterano · Tutor durante 9 años
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(101 Votos)
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To determine which distribution goes with each trait, we need to consider the nature of each trait and how it might be distributed among NFL players. Let's analyze each trait:1. **Age**: The average age is about 25 years old. Age distributions in professional sports often skew younger because athletes tend to peak in their 20s and early 30s. Therefore, the age distribution might be right-skewed (positively skewed), with a longer tail on the older side.2. **Height**: The average height is just over 6'2". Height tends to follow a normal distribution in populations, including athletes, because most people are around the average height with fewer individuals at the extremes.3. **Weight**: The average weight is a little more than 244 lbs. Like height, weight can also follow a normal distribution, but it might be slightly right-skewed due to the presence of heavier positions like linemen.4. **Salary**: The average salary is slightly less than $1.5M per year. Salaries in professional sports are often highly right-skewed because a small number of players earn significantly more than the average, creating a long tail on the higher end.Given these analyses, here's a possible matching of distributions to traits:- **Age**: Right-skewed distribution- **Height**: Normal distribution- **Weight**: Slightly right-skewed or normal distribution- **Salary**: Highly right-skewed distributionThe shape of the distribution matters because it affects how we interpret averages and other statistical measures. For example, in a right-skewed distribution, the mean is greater than the median, which can give a misleading impression of the "average" if not considered carefully. Understanding the distribution helps in making more accurate predictions and decisions based on the data.