In at least 150 words, provide a comprehensive explanation of the key differences between regression and time series analysis in data science, including the types of data each method is best suited for, the assumptions made by each method, the goals of each method, and any specific techniques or models commonly used in each method. Additionally, discuss any limitations or drawbacks of each method, and provide examples of when each method may be most appropriate to use in real-world data analysis scenarios. Use clear and concise language, examples, and diagrams where necessary to aid in understanding.
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