Point out the correct statement.

The correct answer is D. All of the mentioned.

• The exponent of a normally distributed random variables follows what is called the log-normal distribution. This is because the logarithm of a normally distributed random variable is normally distributed.
• Sums of normally distributed random variables are again normally distributed even if the variables are dependent. This is because the sum of two normally distributed random variables is also normally distributed, and the sum of a normally distributed random variable and a constant is also normally distributed.
• The square of a standard normal random variable follows what is called chi-squared distribution. This is because the square of a standard normal random variable is a chi-squared random variable with one degree of freedom.

Here are some additional details about each of these statements:

• The log-normal distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed. It is often used to model the distribution of data that is skewed to the right, such as the heights of people or the weights of cars.
• The chi-squared distribution is a continuous probability distribution that is often used to model the distribution of the sum of the squares of independent standard normal random variables. It is also used to test the goodness of fit of a distribution to a set of data.

I hope this helps! Let me know if you have any other questions.