Rohan made an error in his model. Explain his error. Include the correct grouping for the model
Without specific information about the model or the error Rohan made, it is difficult to provide a specific answer. However, based on the given information, here is a general approach to explaining Rohan's error and suggesting the correct grouping for his model.
Rohan's error likely pertains to the grouping of variables or data points in his model. Grouping is an essential step in modeling as it helps organize data and allows for the analysis of specific subsets. If Rohan's error lies in grouping, it could be due to one of the following mistakes:
1. Incorrect Variable Grouping: Rohan might have incorrectly grouped variables used in his model. This error could lead to improper calculations or misleading results. For example, if he intended to group customer age into three categories (young, middle-aged, and elderly), but instead divided it into two categories (young and middle-aged), his model would miss valuable insights related to the elderly customers' behavior.
2. Inconsistent Data Grouping: If Rohan's model involves data from different sources or time periods, he may have made an error in grouping the data consistently. In such cases, the model might not accurately capture the underlying patterns or relationships. Rohan needs to ensure that the data points or variables are appropriately grouped based on the intended analysis.
3. Overlapping Grouping: Another potential error is overlapping or redundant grouping in the model. This occurs when variables or data points are assigned to multiple groups, resulting in duplicate or irrelevant information. Overlapping grouping can lead to biased analysis or incorrect interpretations.
To determine the correct grouping for Rohan's model, several factors need to be considered, such as the research objective, the nature of the data, and the available variables. It is crucial to identify the right variables or data points that play a significant role in achieving the desired results. Additionally, the grouping should be logical and consistent with the research context.
It is recommended that Rohan carefully review his model, consider the specific variables and data points, and double-check the grouping methodology to correct his error. Working with a domain expert or seeking assistance from colleagues can also provide valuable insights and help ensure a correct grouping for the model.