STA351 Books

**Author:** KO Obisesan

**School:** University of Ibadan

**Department:** Science and Technology

**Course Code:** STA351

Topics: Biometric Method, Population Genetic, genetics, Gene Proportions, gene Variations, Biometrics, Biological Data, Biological Data Collection, Descriptive Statistics, Sampling, Sampling Distribution, Hypothesis Testing, Analysis of Variance, ANOVA.Clinical Trials, Biological Assay, Bioassay, Life Table, Life Table Analysis

**Author:** Michael de Smith

**School:** University of Ibadan

**Department:** Science and Technology

**Course Code:** STA231, STA322, STA351, STA415

Topics: Statistical Analysis, statistical data, statistical method, sampling, sample size, data preparation, data cleaning, missing data, data errors, statistical error, probability theory, odds, risk, frequentist probability theory, Bayesian probability theory, probability distribution, statistical modelling, computational statistics, inference, bias, confounding, hypothesis testing, statistical significance, confidence intervals, Non-parametric analysis, descriptive statistics, measures of central tendency, statistical indices, key functions, matrix, data transformation, data standardization, Box-cox, power transforms, Freeman-turkey transform, log transform, exponential transforms, logit transform, Normal transform, Z-transform, data exploration, graphic, visualization, exploratory data analysis, randomness, randomization, random numbers, random permutations, correlation, autocorrelation, probability distributions, eestimations, estimators, Maximum likelihood estimation, Bayesian estimation, z-test, T-test, variance test, contigency tables, randomized block designs, factorial designs, Analysis of variance, Analysis of covariance, ANOVA, MANOVA, ANCOVA, regression, smoothing, time series analysis

A first course in statistics ,12th edition

**Author:** James McClave, Terry Sincich

**School:** University of Ibadan

**Department:** Science and Technology

**Course Code:** STA351

Topics: statistics, statistical thinking, probability, random variables, probability distributions, inference, population, population means, simple linear regression, probabilistic models

An introduction to generalized linear models ,4th edition

**Author:** Annette Dobson, Adrian Barnett

**School:** University of Ibadan

**Department:** Science and Technology

**Course Code:** STA351

Topics: generalized linear models, Model Fitting, Exponential Family, estimation, inference, normal linear models, Binary Variables, Logistic Regression, Nominal Logistic Regression, Ordinal Logistic Regression, Poisson Regression, Log-Linear Models, Survival Analysis, Clustered data, Longitudinal Data, Bayesian Analysis, Markov Chain Monte Carlo Methods

**Author:** Mark Woodward

**School:** University of Ibadan

**Department:** Science and Technology

**Course Code:** STA351

Topics: Epidemiology, Assessing risk factors, risk, relative risk, analytical procedures, Confounding, interaction, Cohort studies, Caseâ€“control studies, Intervention studies, Sample size determination, Modelling quantitative outcome variables, Modelling binary outcome data, modelling, Modelling follow-up data, Meta-analysis, risk scores, clinical decision rules, Computer-intensive methods

Generalized Linear Models ,2nd Edition

**Author:** McCullagh, John Nelder

**School:** University of Ibadan

**Department:** Science and Technology

**Course Code:** STA351

Topics: Generalized Linear Models, dilution assay, probit analysis, logit models, log-linear models, inverse polynomical, survival data, model fittinf, residuals, pearson residual, Anscombe residual, deviance residual, error structure, systemic component, aliasing, estimation, tables, binary data, binomial distribution, over-dispersion, measurement scales, multinomial distribution, likelihood functions, log-linear models, multiple responses, conditional likelihoods, hypergeometric distributions, Gamma distribution, Quasi-likelihood functions, dependent observations, optimal estimating functions, optimality criteria, model checking, survival data, dispersion

Introduction to Business Statistics ,7th edition

**Author:** Ronald Weiers

**School:** University of Ibadan

**Department:** Science and Technology

**Course Code:** STA351

Topics: Business Statistics, data collection, sampling methods, probability, discrete probability distribution, continous probability distributions, sampling distributions, estimation, hypothesis testing, hypothesis tests, analysis of variance, Chi-square applications, nonparametric methods, regression, simple linear regression, correlation, multiple regression, multiple correlation, model building, time series, forecasting, decision theory, total quality management

Modelling binary data ,2nd edition

**Author:** David Collett

**School:** University of Ibadan

**Department:** Science and Technology

**Course Code:** STA351

Topics: Statistical inference, binary data, Modelling binary data, binomial data, Model checking, bioassay, Overdispersion, exact methods

Introduction to Linear Regression Analysis ,5th edition

**Author:** Elizabeth Peck, Geoffrey Vining, Douglas Montgomery

**School:** University of Ibadan

**Department:** Science and Technology

**Course Code:** STA351

Topics: Linear Regression Analysis, Regression, Model Building, Data Collection, Simple Linear Regression Model, Simple Linear Regression, Least-Squares Estimation, Hypothesis Testing, Interval Estimation, Multiple Regression Models, Multiple linear regression, Hypothesis Testing, Confidence Intervals, Standardized Regression Coefficients, Multicollinearity, Residual Analysis, model adequacy checking, Variance-Stabilizing Transformations, Generalized Least Squares, Weighted Least Squares, Regression Models, subsampling, Leverage, Measures of Influence, influence, Polynomial regression Models, Piecewise Polynomial Fitting, Nonparametric Regression, Kernel Regression, Locally Weighted Regression, Orthogonal Polynomials, Indicator Variables, Multicollinearity, Multicollinearity Diagnostics, Model-Building, regression models, Linear Regression Models, Nonlinear Regression Models, Nonlinear Least Squares, Logistic Regression Models, Poisson regression, Time Series Data, Detecting Autocorrelation, Durbin-Watson Test, Time Series Regression, Robust Regression, Inverse Estimation

Introduction to Linear Regression Analysis Solutions Manual for 5th edition

**Author:** Ann Ryan, Douglas Montgomery, Elizabeth Peck, Geoffrey Vining

**School:** University of Ibadan

**Department:** Science and Technology

**Course Code:** STA351

Topics: Linear Regression Analysis, Regression, Model Building, Data Collection, Simple Linear Regression Model, Simple Linear Regression, Least-Squares Estimation, Hypothesis Testing, Interval Estimation, Multiple Regression Models, Multiple linear regression, Hypothesis Testing, Confidence Intervals, Standardized Regression Coefficients, Multicollinearity, Residual Analysis, model adequacy checking, Variance-Stabilizing Transformations, Generalized Least Squares, Weighted Least Squares, Regression Models, subsampling, Leverage, Measures of Influence, influence, Polynomial regression Models, Piecewise Polynomial Fitting, Nonparametric Regression, Kernel Regression, Locally Weighted Regression, Orthogonal Polynomials, Indicator Variables, Multicollinearity, Multicollinearity Diagnostics, Model-Building, regression models, Linear Regression Models, Nonlinear Regression Models, Nonlinear Least Squares, Logistic Regression Models, Poisson regression, Time Series Data, Detecting Autocorrelation, Durbin-Watson Test, Time Series Regression, Robust Regression, Inverse Estimation

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