Confidence interval in the context of "Challenger Deep"

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⭐ Core Definition: Confidence interval

In statistics, a confidence interval (CI) is a range of values used to estimate an unknown statistical parameter, such as a population mean. Rather than reporting a single point estimate (e.g. "the average screen time is 3 hours per day"), a confidence interval provides a range, such as 2 to 4 hours, along with a specified confidence level, typically 95%.

A 95% confidence level does not imply a 95% probability that the true parameter lies within a particular calculated interval. The confidence level instead reflects the long-run reliability of the method used to generate the interval. In other words, if the same sampling procedure were repeated 100 times from the same population, approximately 95 of the resulting intervals would be expected to contain the true population mean.

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👉 Confidence interval in the context of Challenger Deep

The Challenger Deep is the deepest known point of the seabed of Earth, located in the western Pacific Ocean at the southern end of the Mariana Trench, in the ocean territory of the Federated States of Micronesia.

The GEBCO Gazetteer of Undersea Feature Names indicates that the feature is situated at 11°22.4′N 142°35.5′E / 11.3733°N 142.5917°E / 11.3733; 142.5917 and has an approximated maximum depth of 10,903 to 11,009 m (35,771 to 36,119 ft) below sea level. A 2011 study placed the depth at 10,920 ± 10 m (35,827 ± 33 ft) with a 2021 study revising the value to 10,935 ± 6 m (35,876 ± 20 ft) at a 95% confidence level.

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Confidence interval in the context of World population

In world demographics, the world population is the total number of humans currently alive. It was estimated by the United Nations to have exceeded eight billion in mid-November 2022. It took around 300,000 years of human prehistory and history for the human population to reach a billion and only 218 more years from there to reach 8 billion.

The human population has experienced continuous growth following the Great Famine of 1315–1317 and the end of the Black Death in 1350, when it was nearly 370,000,000. The highest global population growth rates, with increases of over 1.8% per year, occurred between 1955 and 1975, peaking at 2.1% between 1965 and 1970. The growth rate declined to 1.1% between 2015 and 2020 and is projected to decline further in the 21st century. The global population is still increasing, but there is significant uncertainty about its long-term trajectory due to changing fertility and mortality rates. The UN Department of Economics and Social Affairs projects between 9 and 10 billion people by 2050 and gives an 80% confidence interval of 10–12 billion by the end of the 21st century, with a growth rate by then of zero. Other demographers predict that the human population will begin to decline in the second half of the 21st century.

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Confidence interval in the context of Chronology of the universe

The chronology of the universe describes the history and future of the universe according to Big Bang cosmology.

Research published in 2015 estimates the earliest stages of the universe's existence as taking place 13.8 billion years ago, with an uncertainty of around 21 million years at the 68% confidence level.

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Confidence interval in the context of Estimates of historical world population

This article lists current estimates of the world population in history. In summary, estimates for the progression of world population since the Late Middle Ages are in the following ranges:

Estimates for pre-modern times are necessarily fraught with great uncertainties, and few of the published estimates have confidence intervals; in the absence of a straightforward means to assess the error of such estimates, a rough idea of expert consensus can be gained by comparing the values given in independent publications. Population estimates cannot be considered accurate to more than two decimal digits; for example, the world population for the year 2012 was estimated at 7.02, 7.06, and 7.08 billion by the United States Census Bureau, the Population Reference Bureau, and the United Nations Department of Economic and Social Affairs, respectively, corresponding to a spread of estimates of the order of 0.8%.

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Confidence interval in the context of Estimation

Estimation (or estimating) is the process of finding an estimate or approximation, which is a value that is usable for some purpose even if input data may be incomplete, uncertain, or unstable. The value is nonetheless usable because it is derived from the best information available. Typically, estimation involves "using the value of a statistic derived from a sample to estimate the value of a corresponding population parameter". The sample provides information that can be projected, through various formal or informal processes, to determine a range most likely to describe the missing information. An estimate that turns out to be incorrect will be an overestimate if the estimate exceeds the actual result and an underestimate if the estimate falls short of the actual result.

The confidence in an estimate is quantified as a confidence interval, the likelihood that the estimate is in a certain range. Human estimators systematically suffer from overconfidence, believing that their estimates are more accurate than they actually are.

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