1. Many of the continuous random variables that occur in real life are approximately normally distributed. How do you think this helps in studying real life variables? 2. Do you realize and understand the advantage of being able to convert values of an arbitrary normally distributed random variable to the corresponding values of the standard normal variable? If yes, list all the possible advantages of being able to do this. If not what do you plan to do to understand why the standard normal random variable is widely used for computations involving normal distributions?

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Step-by-step explanation:

so firstly, we need to isolate the y variables to be able to solve these inequalities. firstly, add 0.5x on both sides of the first inequality and subtract 1.5x on both sides of the second inequality:

now since the slope is positive for the first inequality, this means that the line going upwards belongs to the first inequality, and the line going downwards belongs to the second inequality.

next, since y ≥ in the first inequality, this means that the shaded region will be above the first inequality's line, thus shading regions a and b.

next, since y ≤ in the second inequality, this means that the shaded region is going to be below this line, thus shading regions a and c.

since both lines shade region a, this means that region a is the solution.

step-by-step explanation:

mark brainliest!