A distinguishing feature of the book is its integration of design and analysis of time series experiments.
Skyrms, B., 267, 290 Slutzky, E., 44 Smith, K.L., 17, 286 Snow, J., 214 Sournerai, S.B., 196 South Carolina ... 45 statistical power Dickey-Fuller test, 146 functions, 243 Neyman-Pearson hypothesis test, 237 Quandt-Andrews method, ...
'Design and Analysis of Time Series Experiments' develops methods and models for analysis and interpretation of time series experiments.
This invaluable reference work: Offers a comprehensive survey of international research designs, methods, and statistical techniques Includes contributions from leading figures in the field Contains data on criminology and criminal justice ...
Inference and hierarchical modeling in the social sciences. Journal of Educational and Behavioral Statistics, 20, 115–147. Draper, N. R., & Smith, H. (1998). Applied regression analysis (3rd ed.). New York: Wiley. Duncan, T. E. ...
... D.N., 399 Huber, P.J., 23 Huijbregts, C.J., 28, 37 Humphries, T.D., 112,393, 399 Hung, Y., 114, 294,399 Hunter, J., 147 Hunter, W., 147 I Iooss, B., 291 J Janssens, M.L., 4 Jeffreys, H., 124 Jin, R., 277–279, 284, 291 Johannesson, ...
Design and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice.
Additionally, the book supplements the classic Box-Jenkins-Tiao model-building strategy with recent auxiliary tests for transformation, differencing, and model selection.
The new edition includes more software examples taken from the three most dominant programs in the field: Minitab, JMP, and SAS.
This second edition of the best-selling Design and Analysis of Ecological Experiments leads these trends with an update of this now-standard reference book, with a discussion of the latest developments in experimental ecology and ...