27.Spatial statistics based on GIS network to forecast yellow starthistle dispersal over time and space in north centre of Idaho. SAS, S-Plus, ArcVIEW and ArcINFO. 2003.
28.EGARCH model for analysis and forecast of Taiwan’s stock variation from 1980’s to current. SAS and S-Plus. 2003—2004
29.Bacterial data analysis with 158 observations and 12 variables in Idaho. SAS and Excel. 2003.
30.Water quality survey of six states in the Pacific Northwest. Logistic model. SAS.2002--2004.
31.Logistic model on cow pregnancy data with 9 farms in Idaho.SAS.2002--2004.
32.Logistic model with MCMC and Bayesian technique on a dose-response data in Idaho. SAS, S-PLUS, and C++.2002.
33.Discrimination analyses for image classification of yellow starthistle in Idaho. SAS, C++ programming and remote sensing imagery technology. 2002.
34.Multiple regressions on a diary data in Idaho with 47 variables and 486 observations. SAS. 2002.
35.Physical education comparison survey between American high school students and Chinese ones. Questionnaire. SAS and Excel. 2003.
36.Creation and implementation of the database structures, data entry programs, coding schemes and validation on water survey data in the Pacific Northwest, also combined with Internet technology for statistical analyses. MySQL, PHP, Html, Linux and Windows. 2002--2004.
26、Tian, Fei, T. S. Prather, B. Shafii, W. J. Price, and L. W. Lass. 2005. Modeling yellow starthistle dispersal in canyon grasslands of Idaho. Abstract. Weed Science Society of America, 45: 120.
27、Tian, F., B. Shafii, C. J. Williams, T. S. Prather, W. J. Price, and L. W. Lass. 2004. Prediction of yellow starthistle survival and movement over time and space. Pages 74-96 in Proceedings of the Sixteenth Annual Kansas State University Conference on Applied Statistics in Agriculture. Manhattan, KS: Kansas State University.
6.Tian, F., T. S. Prather, B. Shafii, W. J. Price, and L. W. Lass. 2005. Modeling yellow starthistle dispersal in canyon grasslands of Idaho. Presented at the 45th Annual Meeting of the Weed Science Society of America, February 7 - 10, 2005, Honolulu, Hawaii.
7.Tian, F., B. Shafii, T. S. Prather, W. J. Price, C. Williams, and L. W. Lass. Dispersal of Yellow Starthistle can be Predicted from Community Susceptability. Paper presented at the 57th meeting of the Western Society of Weed Science, March 9-11, Colorado Springs, Colorado.
8.Tian, F., B. Shafii, C. J. Williams, T. S. Prather, W. J. Price, and L. W. Lass. Prediction of yellow starthistle survival and movement over time and space. Paper presented at the Sixteenth Annual Kansas State University Conference on Applied Statistics in Agriculture, April 25-27, 2004. Manhattan Kansas.
◦Spatial statistics based on GIS network to forecast yellow starthistle dispersal over time and space in north centre of Idaho. SAS, S-Plus, ArcVIEW and ArcINFO. 2003.
◦EGARCH model for analysis and forecast of Taiwan’s stock variation from 1980’s to current. SAS and S-Plus. 2003—2004
◦Bacterial data analysis with 158 observations and 12 variables in Idaho. SAS and Excel. 2003.
Water quality survey of six states in the Pacific Northwest. Logistic model. SAS.2002--2004.
Logistic model on cow pregnancy data with 9 farms in Idaho.SAS.2002--2004.
Logistic model with MCMC and Bayesian technique on a dose-response data in Idaho. SAS, S-PLUS, and C++.2002.
◦Discrimination analyses for image classification of yellow starthistle in Idaho. SAS, C++ programming and remote sensing imagery technology. 2002.
◦Multiple regressions on a diary data in Idaho with 47 variables and 486 observations. SAS. 2002.
Physical education comparison survey between American high school students and Chinese ones. Questionnaire. SAS and Excel. 2003.
◦Multiple regression and principle component analysis on a dairy data in Idaho with 47 variables and 486 observations for dairy nutrition analysis. SAS. 2002.
◦Logistic model with MCMC and Bayesian techniques on a dose-response data in Idaho. SAS, S-Plus, and C++. 2002.
◦Creation and implementation of the database structures, data entry programs, coding schemes and validation on water survey data in the Pacific Northwest, also combined with Internet technology for statistical analyses. MySQL, PHP, Html, Linux and Windows. 2002--2004.
◦Creation and implementation of the database structures, data entry programs, coding schemes and validation for the search of the publication and presentation records from the Statistical Programs by means of web pages. MySQL, PHP, Html, Linux and Windows.2002--2003.