However, sometimes a normal curve is not the most detailed way of allotting data either. Nonetheless, forming a normal curve can help determine whether the data will fit into it and follow the normal curve’s Empirical Rule. The Empirical Rule of normal circulation for a normal curve states that 68% of the data should dip within one standard deviation of the mean and 16% should deceit to each side. However, 91.7% of the data from this report deceit within one standard deviation of the mean and exactly no data deceits further left than that. That said, a normal curve formed from this data would be greatly biased to the right because 72.9% of the data dips left of the mean, even if it’s only one standard deviation left. In other words, the data does not follow the Empirical Rule and does not suit with a normal
However, sometimes a normal curve is not the most detailed way of allotting data either. Nonetheless, forming a normal curve can help determine whether the data will fit into it and follow the normal curve’s Empirical Rule. The Empirical Rule of normal circulation for a normal curve states that 68% of the data should dip within one standard deviation of the mean and 16% should deceit to each side. However, 91.7% of the data from this report deceit within one standard deviation of the mean and exactly no data deceits further left than that. That said, a normal curve formed from this data would be greatly biased to the right because 72.9% of the data dips left of the mean, even if it’s only one standard deviation left. In other words, the data does not follow the Empirical Rule and does not suit with a normal