Applied Statistical Methods in Agriculture, Health and Life Sciences

Inbunden, Engelska, 2014

AvBayo Lawal

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This textbook teaches crucial statistical methods to answer research questions using a unique range of statistical software programs, including MINITAB and R. Subjects covered include among others data description, probability distributions, experimental design, regression analysis, randomized design and biological assay.

Produktinformation

Utgivningsdatum2014-09-24
Mått155 x 235 x 49 mm
Vikt1 378 g
FormatInbunden
SpråkEngelska
Antal sidor799
Upplaga2014
FörlagSpringer International Publishing AG
ISBN9783319055541

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Bayo Lawal is Professor of Statistics at Kwara State University, Malete, Kwara State Nigeria. He received his B.Sc. (Hons) degree in Mathematics from the Ahmadu Bello University, Nigeria and his Master’s degree in Biometry from the University of Reading, UK. His Ph.D. in Statistics is from the University of Essex, UK. Professor Lawal has taught for several years at the University of Ilorin, Nigeria, St Cloud State University, St Cloud, MN, Temple University in Philadelphia, USA. He was a visiting professor in the department of Biometry and Epidemiology (now department of Biostatistics) at the Medical University of South Carolina, Charleston, SC between 2009 and 2000. He also served as chair of the Departments of Statistics at St Cloud State University, MN, USA and at the University of Ilorin in Nigeria. He has also served as Dean of the School of Sciences, Auburn University at Montgomery between 2004 and 2008 as well as the Dean of the School of Arts and Sciences, and Interim Academic Vice-President at the America University of Nigeria, Yola, Nigeria between 2008 and 2011. He is currently serving as head of the Department of Statistics and Mathematical Sciences at Kwara State University, Malete, Nigeria.

Table of Contents attached as well. Introduction.- Frequency Distributions.- Numerical Description of Data.- Probability and Probability Distributions.- Estimation and Hypothesis Testing.- Regression Analysis.- Categorical Data Analysis.- Experimental Design.- The Completely Randomized Design.- The Randomized Complete Block Design.- Multiple Blocking Designs.- Analysis of Covariance.- Factorial Treatments Designs.- The Split-Plot Design.- Incomplete Block Design.- Quantal-Bioassay.- Repeated Measures Design.- Survival Analysis.