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Introduction to Life Tables

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  Introduction to Life Tables  Definition :   A life table is a statistical tool used in demography and actuarial science to summarize mortality patterns in a population.   Purpose : i) Provides a snapshot of mortality conditions. ii) Helps in estimating survival probabilities for different age groups. iii) Essential for demographic studies, insurance, and public health planning.   Key Components of Life Tables   Radix (Base Population) : The starting number of individuals (often set at 100,000) to track mortality over time.   Age Intervals : The life table is divided into age groups (e.g., 0-1, 1-5, 5-10, etc.). Helps in analyzing mortality trends across different life stages   Probability of Dying (qx) : Denoted as qx , it represents the probability that a person of age x will die before reaching age x+1 . Computed from observed mortality data   Number of Survivors (lx) : Denoted as lx , it rep...

Ratio and Regression Method of Estimation

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  2.4 Ratio Method   Concept and rationale of Auxiliary Variable An auxiliary variable is an additional variable that is related to the main variable of interest in a statistical study but is not directly of interest itself. It is often used to improve the efficiency of an estimation process. The auxiliary variable is known or observed alongside the variable of interest and helps in reducing the variance of the estimates when used appropriately. The ratio method is most effective in situations where the auxiliary variable is easy to measure, and there is a strong linear relationship between the auxiliary and study variables. The method works best when the ratio of the two variables remains relatively stable across the population. Rationale for Using Auxiliary Variables Improving Precision : Auxiliary variables can significantly reduce the variance of the estimators, leading to more precise estimates. This is particularly useful when direct measurements of the main ...

Cluster Sampling, Idea of two stage sampling and Multi stage sampling

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  2.2 Cluster Sampling   It is one of the basic assumptions in any sampling procedure that the population can be divided into a finite number of distinct and identifiable units, called sampling units. The smallest units into which the population can be divided are called elements of the population. The groups of such elements are called clusters. In many practical situations and many types of populations, a list of elements is not available and so the use of an element as a sampling unit is not feasible. The method of cluster sampling or area sampling can be used in such situations.   In cluster sampling, -Divide the whole population into clusters according to some well-defined rule. -Treat the clusters as sampling units. -Choose a sample of clusters according to some procedure. -Carry out a complete enumeration of the selected clusters, i.e. collect information on all the      sampling units available in selected clusters.   Area...