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Informationen zum Autor E.L. Clarke's early writing days were most productive when she was sitting on a train going to work. Writing in a cafe or on her lounge are top seconds, spurring her creativity, and are much preferred than writing in the wee pre-dawn hours which has become the norm for a busy mum and businesswoman trying to eke out time in the day for her craft. A methodical and practical person who enjoys planning parts of her books in a spreadsheet, writing novels has taught E.L. to let go a bit. All inspiration for her books has come purely from her imagination. She feels that sometimes it's as if someone else wrote her stories, saying, "I look back on my manuscripts at times and wonder Wow, where did THAT come from?"E.L. believes that a great book is based on strong characters and a gripping storyline-something that is relatable enough to keep the reader interested but unique enough to allow the reader to escape. She hopes that her own stories provide her young readers a world to get temporarily lost in, to understand universal friendship, and that there could be so much more in the world than what is presented to us day to day. When she isn't writing thought-provoking fantasy and science fiction stories for young adults, E.L. manages a small photography business and enjoys singing, playing piano, camping, snowboarding, hiking, cooking, motorcycle riding, drawing and exploring the outdoors near Sydney, Australia where she lives with her husband, children, and their pets-a black Labrador, and a Maine Coon cat. Verntropa: The Balance is her debut novel, the first volume in the Verntropa trilogy. Klappentext Contains a detailed explanation of how to undertake and interpret computer analysis using the SAS package. This book includes worked examples as well as exercises at the end of each chapter. The authors provide full coverage of the basic principles behind the planning and analysis of experiments, without being too theoretical and using a practical approach. Inhaltsverzeichnis Preface. 1 Collecting data by experiments. 1.1 Introduction. 1.2 Experiments. 1.3 Measurements of yield or response. 1.4 Natural variation in data. 1.5 Initial data analysis. 1.6 General applications of experimentation. 1.7 Exercises. 2 Basic statistical methods: the normal distribution. 2.1 Statistical inference for one sample of normally distributed data. 2.2 Hypothesis test. 2.3 Comparison of two samples of normally distributed data. 2.4 The F -test for comparing two estimated variances. 2.5 Confidence interval for the difference between two means. 2.6 'Paired data' t -test when samples are not independent. 2.7 Linear functions of normally distributed variables. 2.8 Linear models including normal random variation. 2.9 Exercises. 3 Principles of experimental design. 3.1 Introduction. 3.2 Treatment structure. 3.3 Changing background conditions - the need for comparison. 3.4 Replication. 3.5 Randomization. 3.6 Blocking. 3.7 Sources of variation. 3.8 Planning the size of an experiment. 3.9 Exercises. 4 The analysis of data from orthogonal designs. 4.1 Introduction. 4.2 Comparing treatments. 4.3 Confidence intervals. 4.4 Homogeneity of variance. 4.5 The randomized complete block. 4.6 Duncan's multiple range test. 4.7 Extra replication of important treatments. 4.8 Contrasts among treatments. 4.9 Latin squares and other orthogonal designs. 4.10 Graeco-Latin squares. 4.11 Two fallacies. 4.12 Assumptions in analysis: using residuals to examine them. 4.13 Transformations. 4.14 Theory of variance stabilization. 4.15 Missing data in block designs. 4.16 Exer...
