discussion response needed below statement.

The normal curve, Z-distribution, and T-distribution were discussed further this week, and I had to do more research for this discussion. The normal curve is symmetrical, unimodal, has a common value for the mean, median, and mode, has a continuous range from negative infinity to positive infinity, and has a total area under the curve equal to 1. I have limited experience utilizing this, but I remember when I was in school our teachers would use this for test scores. I was unaware that it was common for teachers to use it so often until I read, "The normal distribution, or bell curve, is most familiar and useful to teachers in describing the frequency of standardized test scores, how many students earned scores. This is not just any distribution, but a theoretical one with several unique characteristics" (SUNY Cortland). I can see how this can be beneficial, especially from a visual perspective and the way it is depicted. The standard normal distribution is represented in z-scores. Z-scores are often called standard scores. "Sometimes it is helpful to think of z scores as just another unit of measurement... when we work with z scores, we're basically converting our existing data into a new unit of measurement: standard deviation units. All interval/ratio data can be expressed as z scores" (The Normal Distribution). T-distribution is continuous, symmetrical, and used to compare data from samples to the assumed normal distribution of the data of the population. I mentioned previously that many teachers use this, but it can be useful in a healthcare setting as well. Note that the normal curve is a key tool when analyzing data.