(1) Draw a standard normal curve which is a bell-shaped curve centered at 0 . (2) Mark the Z-score of -1.53 on the horizontal axis. (3) Since we want the probability greater than -1.53 , shade the area to the right of -1.53 under the curve.

To truly appreciate the standard normal curve, it's worth noting that it emerged from the work of mathematicians like Carl Friedrich Gauss in the early 19th century. This bell-shaped curve not only describes the distribution of many natural phenomena, such as heights and test scores, but also serves as the foundation for inferential statistics, providing insights into probability and data analysis. When applying the standard normal curve in real-world scenarios, consider how businesses use it for quality control. For instance, a manufacturer might analyze the distribution of product dimensions, using the normal curve to determine what percentage falls within acceptable limits. This way, they can identify outliers, improve processes, and ensure consistency in their products—making the math not just theoretical, but practically impactful!