Concepts of Regression Analysis and Statistical Methods

This book aims to provide the reader with useful information in the realm of simple linear regression: parameter estimation and model fitting; prediction; inference about parameters; linear correlation and inference about correlation coefficient; multiple linear regression model: model assumptions, parameter estimation; coefficient of multiple determination; partial correlation coefficients; partitioning sum of squares, ANOVA table construction, test of hypothesis, prediction, dummy...
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This book aims to provide the reader with useful information in the realm of simple linear regression: parameter estimation and model fitting; prediction; inference about parameters; linear correlation and inference about correlation coefficient; multiple linear regression model: model assumptions, parameter estimation; coefficient of multiple determination; partial correlation coefficients; partitioning sum of squares, ANOVA table construction, test of hypothesis, prediction, dummy variables; residual analysis: assessing the model assumptions. Statistical estimation and statistical hypothesis testing; sampling distribution of: the sample mean, sample proportion, sample variance, difference between two sample means, difference between two sample proportions and the ratio of two sample variances; inference about: the population mean, population proportion and the population variance; comparison of: two population means, two population proportions, two population variances; paired versus independent population comparisons; sample size determination; statistical test of hypothesis about equality of more than two population means, multiple-comparison method; chi-square test of association and homogeneity; non-parametric methods. Generally, this book deals with concept of Regression Analysis and Statistical Methods.