The normal or Gaussian distribution (aka Bell Curve or Normal Curve) is the basis for understanding, plotting and calculating z-scores and their probabilities. The more familiar you are with the properties of the normal distribution, the better your foundation for working with z-scores will be. For instance, knowing that a normal distribution has a mean of 0 and a standard deviation of 1 is key to being able to detect if your calculations and their results are reasonable or not. Additionally, knowing that a z-score is literally the number of standard deviation units from the mean sets you up to be successful in understanding homework, quiz, and exam questions. It is evident in the formula for z-score: x-mean/sd. No matter what value we obtain on the top, we know that dividing the numerator by the denominator standardizes that result based on the standard deviation. So, as a simple example, a numerator of 10-5, or 5 is the distance from the mean, i.e. the value of interest is 5 points higher than the given mean (also known as a deviation score). But a positive difference/distance of 5 has little meaning with an unclear or undefined context. Once we know the denominator, we have the full context. If we assume that the denominator is 2.5, for example, we know immediately that the distance of 5 is 2 standard deviation units above the mean (evidenced by the fact that the x-value was 10 and that the deviation score of 5 is positive rather than negative, Dividing 5 by 2.5 immediately tells us that the z-score is 2.0.
The first rule of working with statistics and their distributions is to "know what to expect". For instance, one characteristic of the Gaussian distribution is that 95% of all scores in a distribution fall within 1.96 standard deviations, or just under 2 standard deviations from the mean (or that 95.5% of all scores fall between 2 standard deviations from them mean. By knowing that, we can already expect that the area of interest is greater than 50% (given the normal distribution is split in half, with 50% of the distribution falling below and the other 50% falling above the mean (i.e. z-score of 0). It is important to also be aware of how much of the distribution falls between 1, 2, and 3 standard deviations from the mean, and that 99.7% of all values of any normal distribution fall within 3 standard deviation units from the mean, i.e. have a z-score of 3.0.
Instead of providing the answers, I would suggest doing a few things. First, find a depiction of the normal distribution that has the percentages associated with 1, 2, and 3 standard deviations (see here for a clear example: https://analystprep.com/cfa-level-1-exam/quantitative-methods/key-properties-normal-distribution/). By having this information, knowing the z-score formula, and understanding how z-scores work, you should be able to answer most of the questions asked. At the same time, understanding that combining two areas (proportions/probabilities) together, represented by two z-scores (e.g. -1.38 and +1.38), provides answers to questions regarding area between two z-scores, as well as areas outside of the two z-scores, combined.
This, along with examples from a google search, and especially now with AI, you should be able to calculate and interpret, as well as provide a reasoning for the answers you obtain. I can say with 100% certainty, that the answer to the last question is a definitive "No", assuming calculations were performed correctly. If you wan to see how each of the answers to the prior questions are obtained, simply respond to this answer and I will write back. Additionally, be sure you have evidence that you have tried to already answer these yourself first.
Thinking through the problem independently is a much more effective method, and a longer retention of the information acquired, than just being given the answers. Finally, learning the principles or rules of statistics and probability, in this case for the z-score, will serve you well far beyond a single assignment or a few sample questions.
