Có một số các cuốn sách có sẵn mô tả các ứng dụng thú vị của các số liệu thống kê về khoa học môi trường. Thống kê hàng loạt cuốn sách trong môi trường là một điểm khởi đầu tốt đẹp bởi vì nó có chứa các giấy tờ phát sinh từ cuộc hội thảo với các chủ đề khác nhau bao gồm giám sát môi trường, ô nhiễm và ô nhiễm, biến đổi khí hậu và khí tượng học, tài nguyên nước, thủy sản và lâm nghiệp, bức xạ, và chất lượng không khí (Barnett và dân Thổ. | CHAPTER 12 Final Remarks There are a number of books available describing interesting applications of statistics in environmental science. The book series Statistics in the Environment is a good starting point because it contains papers arising from conferences with different themes covering environmental monitoring pollution and contamination climate change and meteorology water resources fisheries and forestry radiation and air quality Barnett and Turkman 1993 1994 1997 . Further examples of applications are also provided by Fletcher and Manly 1994 Fletcher et al. 1998 and Nychka et al. 1998 . For more details about statistical methods in general the handbook edited by Patil and Rao 1994 or the Encyclopedia of Environmetrics El-Shaarawi and Piegorsch 2001 are good general references. There are several journals that specialize in publishing papers on applications of statistics in environmental science with the most important being Environmetrics Ecological and Environmental Statistics and The Journal of Agricultural Biological and Environmental Statistics. In addition journals on environmental management frequently contain papers on statistical methods. It is always risky to attempt to forecast the development of a subject area. No doubt new statistical methods will continue to be proposed in all of the areas discussed in this book but it does seem that the design and analysis of monitoring schemes time series analysis and spatial data analysis will receive particular attention as far as research is concerned. In particular approaches for handling temporal and spatial variation at the same time are still in the early stages of development. One important topic that has not been discussed in this book is the handling of the massive multivariate data sets that can be produced by automated recording devices. Often the question is how to reduce the data set to a smaller but still very large set that can be analysed by standard statistical methods. There are many future
