What is a real world situation a data scientist would use scatterplots? Identify the outliers and clusters? Explain why you chose to be a data scientist
A real world situation where a data scientist would use scatterplots is in analyzing sales data for a retail company. By creating a scatterplot of sales revenue against different factors such as promotional spending, customer demographics, or seasonal trends, a data scientist can identify outliers and clusters within the data.
For example, if there is a cluster of data points representing high sales revenue during a specific time period, the data scientist might investigate the underlying reasons for this cluster, such as a successful marketing campaign or a new product launch. On the other hand, if there are outlier data points representing unusually low sales revenue, the data scientist could delve deeper into these points to understand any underlying issues or anomalies in the data.
As for why I chose to be a data scientist, I have always been drawn to the power of data and its ability to uncover insights and patterns that can drive decision-making and solve complex problems. Being a data scientist allows me to utilize my analytical skills and passion for problem-solving to make a meaningful impact in various industries and help organizations make data-driven decisions. Additionally, the constantly evolving nature of data science provides opportunities for continuous learning and growth, which I find personally fulfilling.