Estimation and Forecasting in Time Series

This lecture covers the concepts of estimation and forecasting in time series analysis, starting with a discussion on real data analysis to motivate the study of seasonal and time series models. The instructor presents sea surface temperature data as a case study, highlighting the importance of understanding global climate systems. The lecture delves into the process of estimating parameters using methods like least squares and maximum likelihood, emphasizing the significance of model comparison and selection using information criteria. The session concludes with an introduction to forecasting future values in time series, discussing the practical implications of predicting climate trends and making informed decisions based on forecasted data.