This course is tailored to delve into the fascinating world of probability distribution models in statistics, with a special emphasis on utilizing Microsoft Excel as a tool for analysis. Designed for students from diverse academic backgrounds, the course aims to demystify how mathematical models describe and interpret data. It begins with an introduction to understanding data shapes, a cornerstone in the study of statistics. Students will explore the three essential pillars for describing a distribution: shape, center, and spread. The course illuminates various data shapes and their significance in statistical analysis. This includes understanding skewed distributions, such as salary distributions in corporations, and characteristic distributions, like intervals between cars at a tollbooth or atom decay. The course vividly explains different types of data shapes, including single-peaked histograms, symmetric distributions, right and left-skewed distributions, and bimodal distributions, providing students with a comprehensive view of how data can be represented. An integral part of the course is the mathematical description of these data shapes. Students will delve into the realms of uniform distributions, represented by scenarios like rolling a fair die, Poisson distributions that model events in fixed intervals such as cars arriving at an intersection, and exponential distributions that portray time between events like radioactive decay. The relationship between Poisson and exponential distributions is a key focus, offering insights into the intricacies of statistical modeling. Furthermore, binomial distributions, representing the number of successes in a fixed number of trials, will be covered, exemplifying through scenarios like sales calls. The course emphasizes the importance of these mathematical models in facilitating quantitative analysis, aiding in making predictions, and assisting in comprehending underlying phenomena. By understanding the shape of data, students will learn that statistics is more than just numbers; it's about interpreting these numbers to make informed decisions and predictions. In conclusion, this course is designed to provide students with a holistic view of data, combining shape, center, and spread to offer a complete picture of statistical analysis. The application of these concepts in Microsoft Excel not only enhances the learning experience but also equips students with practical skills essential in the modern data-driven world.