Some Implications of Truncating the N(1, 考2) Distribution to the left at Zero

作者：Iheanyi S Iwueze

来源：Journal of Applied Sciences, 2007.

• Truncation
• probability limits
• skewness
• kurtosis

In this research, we want to present the N(1, 考2) distribution when its values do not admit values less than or equal to zero. The 0.001 probability limits were used to give practical assurance that the values from N(1, 考2) are all positive. The truncated values are greater than zero if and only if 0%26lt;考%26lt;0.30. The expression for the mean of the left-truncated N(1, 考2) distribution is in terms of the cumulative distribution function of the standard normal distribution, while that of the variance is in terms of the Chi-square distribution with one degree of freedom. The logarithmic transform of the left-truncated N(1, 考2) distribution was found to be approximately normal when 考%26lt;0.10.

• 出版日期2007