Complete Life Table (Tabel Kematian Lengkap)

A Complete Life Table is an important statistical and demographic tool used to describe the pattern of survival and mortality in a population. It provides detailed information about the probability of death, the number of survivors, and life expectancy at each exact age interval, usually one year. In public health, epidemiology, actuarial science, and population studies, the complete life table helps researchers understand how mortality changes across the lifespan. By using a hypothetical cohort, often beginning with 100,000 births, the table illustrates the survival experience of a population from birth until the oldest ages.

The construction of a complete life table involves several interrelated statistical components, including the probability of dying (nqx), the number surviving (lx), the number dying (ndx), person-years lived (nLx), and life expectancy (ex). These components are calculated sequentially, meaning that the value in one column depends on the results of previous calculations. Therefore, accuracy and consistency are very important during the computation process. Compared with an abridged life table, which uses grouped age intervals such as five-year categories, the complete life table provides more detailed and precise estimates because it uses single-year age intervals.

For statistics students, learning about the complete life table is essential because it introduces the application of statistical methods in real-world population analysis. Through life table analysis, students can understand survival analysis, mortality measurement, and estimation techniques commonly used in health and social research. In addition, complete life tables are widely applied in estimating life expectancy, evaluating public health programs, projecting populations, and supporting insurance and pension calculations. Therefore, understanding the principles and calculations of complete life tables forms an important foundation for advanced studies in biostatistics, demography, and epidemiology.