Library Of American University Of Madaba
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Kaltenbach, Hans-Michael.
A Concise Guide to Statistics [electronic resource] / by Hans-Michael Kaltenbach. - XIII, 111p. 33 illus. online resource. - SpringerBriefs in Statistics .
Basics of Probability Theory -- Estimation -- Hypothesis Testing -- Regression -- References -- Index.
The text gives a concise introduction into fundamental concepts in statistics. Chapter 1: Short exposition of probability theory, using generic examples. Chapter 2: Estimation in theory and practice, using biologically motivated examples. Maximum-likelihood estimation in covered, including Fisher information and power computations. Methods for calculating confidence intervals and robust alternatives to standard estimators are given. Chapter 3: Hypothesis testing with emphasis on concepts, particularly type-I , type-II errors, and interpreting test results. Several examples are provided. T-tests are used throughout, followed important other tests and robust/nonparametric alternatives. Multiple testing is discussed in more depth, and combination of independent tests is explained. Chapter 4: Linear regression, with computations solely based on R. Multiple group comparisons with ANOVA are covered together with linear contrasts, again using R for computations.
9783642235023
Statistics.
Statistics.
Statistics, general.
Statistics for Life Sciences, Medicine, Health Sciences.
QA276-280
519.5
A Concise Guide to Statistics [electronic resource] / by Hans-Michael Kaltenbach. - XIII, 111p. 33 illus. online resource. - SpringerBriefs in Statistics .
Basics of Probability Theory -- Estimation -- Hypothesis Testing -- Regression -- References -- Index.
The text gives a concise introduction into fundamental concepts in statistics. Chapter 1: Short exposition of probability theory, using generic examples. Chapter 2: Estimation in theory and practice, using biologically motivated examples. Maximum-likelihood estimation in covered, including Fisher information and power computations. Methods for calculating confidence intervals and robust alternatives to standard estimators are given. Chapter 3: Hypothesis testing with emphasis on concepts, particularly type-I , type-II errors, and interpreting test results. Several examples are provided. T-tests are used throughout, followed important other tests and robust/nonparametric alternatives. Multiple testing is discussed in more depth, and combination of independent tests is explained. Chapter 4: Linear regression, with computations solely based on R. Multiple group comparisons with ANOVA are covered together with linear contrasts, again using R for computations.
9783642235023
Statistics.
Statistics.
Statistics, general.
Statistics for Life Sciences, Medicine, Health Sciences.
QA276-280
519.5