A non-calculus based introduction for students studying statistics, business, engineering, health sciences, social sciences, and education. It presents a thorough coverage of statistical techniques and includes numerous examples largely drawn from actual research studies. Little mathematical background is required and explanations of important concepts are based on providing intuition using illustrative figures and numerical examples. The first part shows how statistical methods are used in diverse fields in answering important questions, while part two covers descriptive statistics and considers the organisation and summarisation of data. Parts three to five cover probability, statistical inference, and more advanced statistical techniques.
An Intermediate Course with Examples in S-Plus, R, and SAS Richard M. Heiberger, Burt Holland. (Steel and Torrie, 1960) Steel, R. G. D. and ... (Westfall and Rom, 1990) Westfall, P. H. and Rom, D. (1990). Bootstrap stepdown testing with ...
Imhoff, C., Sousa, R., 1997. The Information Ecosystem. Part 1. DM-Review, January 27. Inmon, W., Imhoff, C., Sousa, R., 1998. Corporate Information Factory. John Wiley & Sons, New York, NY. Juran, J., 1951. Quality Control Handbook.
National Bureau of Standards statistics consultant John Mandel here draws a clear blueprint for statistical analysis, geared to the particular needs of the physical scientist.
This book is a guide to the practical application of statistics to data analysis in the physical sciences.
[Davis (1986b)] Consider the two-sided version of Problem 5.11 in which Ho: p1 = p2 is tested against Hz: p1 # p2. The following five tests reject Ho when T(y, m) > c where the test statistics T(, ) are given below and the constants c ...
This is the first book at the graduate textbook level to discuss analyzing financial data with S-PLUS.
This volume collects the extended versions of papers presented at the SIS Conference “Statistics and Data Science: new challenges, new generations”, held in Florence, Italy on June 28-30, 2017.
This book provides an up-to-date treatment of the foundations common to the statistical analysis of network data across the disciplines.
Everitt, B., & Hothorn, T. (2011). An introduction to applied multivariate analysis with R. New York: Springer. Groves, R., Fowler, F., Couper, M., Lepkowski, J., Singer, E., & Tourangeau, R. (2009). Survey methodology.
A prime example of this is the comparison of health-care interventions, where there is a growing expectation from policymakers that evidence supporting the cost-effectiveness of new interventions be provided along with customary data on ...