Recent Advances In Cluster Sampling Using R Software
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The present book deals with complete introduction of sample survey methodology, its historical background. An introduction of R-software has been given. The regression analysis, correlation analysis and confidence interval are given in numerical summary. In graphic summary box plots, qqnorm plots etc are provided and also four new functions cluster1(x, N), cluster2(x), cluster3(x), DEF1(x) and SRSWOR(Y, N) have been developed and complete codes along with illustrations have been given.In this book an attempt has been made to show that cluster sampling is more efficient than simple random sampl...
The present book deals with complete introduction of sample survey methodology, its historical background. An introduction of R-software has been given. The regression analysis, correlation analysis and confidence interval are given in numerical summary. In graphic summary box plots, qqnorm plots etc are provided and also four new functions cluster1(x, N), cluster2(x), cluster3(x), DEF1(x) and SRSWOR(Y, N) have been developed and complete codes along with illustrations have been given.In this book an attempt has been made to show that cluster sampling is more efficient than simple random sampling provided the mean square within the clusters is maximum and there is a negative intra-class correlation coefficient between elements within clusters as relative efficiency of cluster sampling increases with increase in mean square within clusters. Different estimators of cluster sampling are applied and their results are compared with simple random sampling using the same sample size. Different computer programmes are developed using R-software
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