000 02758cam a2200265 a 4500
008 080326s1996 nyua b 001 0 eng
010 _a96084915
020 _a0412062917
035 _a(Sirsi) u336
040 _aEG-CaNU
_cEG-CaNU
_dEG-CaNU
042 _ancode
082 0 0 _a519.538
_2 22
100 1 _aChristensen, Ronald
_91096
245 1 0 _aAnalysis of variance, design and regression applied statistical methods /
_c Ronald Christensen.
260 _aNew York :
_b Chapman & Hall,
_c 1996.
300 _axvi, 587 p. :
_b ill. ;
_c 26 cm.
504 _aIncludes bibliographical references (p. 576-581) and indexes.
520 _aThis text presents a comprehensive treatment of basic statistical methods and their applications. It focuses on the analysis of variance and regression, but also addressing basic ideas in experimental design and count data. The book has four connecting themes: similarity of inferential procedures, balanced one-way analysis of variance, comparison of models, and checking assumptions. Most inferential procedures are based on identifying a scalar parameter of interest, estimating that parameter, obtaining the standard error of the estimate, and identifying the appropriate reference distribution. Given these items, the inferential procedures are identical for various parameters. Balanced one-way analysis of variance has a simple, intuitive interpretation in terms of comparing the sample variance of the group means with the mean of the sample variance for each group. All balanced analysis of variance problems are considered in terms of computing sample variances for various group means. Comparing different models provides a structure for examining both balanced and unbalanced analysis of variance problems and regression problems. Checking assumptions is presented as a crucial part of every statistical analysis. Examples using real data from a wide variety of fields are used to motivate theory. Christensen consistently examines residual plots and presents alternative analyses using different transformation and case deletions. Detailed examination of interactions, three factor analysis of variance, and a split-plot design with four factors are included. The numerous exercises emphasize analysis of real data. Senior undergraduate and graduate students in statistics and graduate students in other disciplines using analysis of variance, design of experiments, or regression analysis will find this book useful.
650 0 _aElectronics
_96598
650 0 _aRegression analysis.
_96599
650 0 _aAnalysis of variance.
_96600
650 0 _aLinear models (Statistics)
_96601
596 _a1
999 _c2359
_d2359