Question: Review and reflect on the knowledge you have gained from this course. Based on your review and reflection, write at least 3 paragraphs on the following:
Topic 1: Define the patterns and characteristics of time series data. How does this differ from other statistical methods such as linear regression? What is required in the forecasting process?
Topic 2: Define the patterns and characteristics of time series data. How does this differ from other statistical methods such as linear regression? What is required in the forecasting process?
Topic 3: Define the patterns and characteristics of time series data. How does this differ from other statistical methods such as linear regression? What is required in the forecasting process?
Topic 4: Discuss and analyze the purpose and importance of data preparation with regards to time series analysis. What are some indications that a dataset needs additional preparation?
Topic 5: Compare and contrast exponential smoothing methods. What are the commonalities and differences between no seasonal versus seasonal data series? Give some examples where one model would be a better fit over another and why.
Topic 6: Discuss the various Autoregressive Integrated Moving Average (ARIMA) Models. What are the implicit assumptions for each of these models? Give some examples where one model would be a better fit over another and why.
Please help me summarize the above topics: