Trends and patterns in data are visual cues that help us to identify patterns over time or in large data sets. Trends are long-term averages or tendencies in data, while patterns are shorter-term phenomena or relationships between different pieces of data. Examples of trends and patterns include: Trends: -Seasonal trends: These are patterns that emerge over the course of a season, like increased ice cream sales in the summertime. -Price trends: This is the tendency of prices to move in a particular direction over time, such as a general increase in gasoline prices over several years. Patterns: -Time series patterns: This is the observation of particular behaviors occurring at specific times. For example, a person’s email usage may peak on Monday mornings and taper off over the course of the week. -Cluster patterns: These are observed relationships between different items or variables, like a correlation between the number of ice cream sales and the number of sunny days.