Scientific consensus on climate changeThere is a strong scientific consensus that the Earth is warming and that this warming is mainly caused by human activities. This consensus is supported by various studies of scientists' opinions and by position statements of scientific organizations, many of which explicitly agree with the Intergovernmental Panel on Climate Change (IPCC) synthesis reports. Nearly all actively publishing climate scientists say humans are causing climate change. Surveys of the scientific literature are another way to measure scientific consensus.
MedianIn statistics and probability theory, the median is the value separating the higher half from the lower half of a data sample, a population, or a probability distribution. For a data set, it may be thought of as "the middle" value. The basic feature of the median in describing data compared to the mean (often simply described as the "average") is that it is not skewed by a small proportion of extremely large or small values, and therefore provides a better representation of the center.
SeasonA season is a division of the year based on changes in weather, ecology, and the number of daylight hours in a given region. On Earth, seasons are the result of the axial parallelism of Earth's tilted orbit around the Sun. In temperate and polar regions, the seasons are marked by changes in the intensity of sunlight that reaches the Earth's surface, variations of which may cause animals to undergo hibernation or to migrate, and plants to be dormant.
Media coverage of climate changeMedia coverage of climate change has had effects on public opinion on climate change, as it conveys the scientific consensus on climate change that the global temperature has increased in recent decades and that the trend is caused by human-induced emissions of greenhouse gases. Climate change communication research shows that coverage has grown and become more accurate. Some researchers and journalists believe that media coverage of politics of climate change is adequate and fair, while a few feel that it is biased.
Median absolute deviationIn statistics, the median absolute deviation (MAD) is a robust measure of the variability of a univariate sample of quantitative data. It can also refer to the population parameter that is estimated by the MAD calculated from a sample. For a univariate data set X1, X2, ..., Xn, the MAD is defined as the median of the absolute deviations from the data's median : that is, starting with the residuals (deviations) from the data's median, the MAD is the median of their absolute values. Consider the data (1, 1, 2, 2, 4, 6, 9).
Swiss AlpsThe Alpine region of Switzerland, conventionally referred to as the Swiss Alps (Schweizer Alpen, Alpes suisses, Alpi svizzere, Alps svizras), represents a major natural feature of the country and is, along with the Swiss Plateau and the Swiss portion of the Jura Mountains, one of its three main physiographic regions. The Swiss Alps extend over both the Western Alps and the Eastern Alps, encompassing an area sometimes called Central Alps.
AlpsThe Alps (ælps) are the highest and most extensive mountain range that is entirely in Europe, stretching approximately across eight Alpine countries (from west to east): Monaco, France, Switzerland, Italy, Liechtenstein, Germany, Slovenia, and Austria. The Alpine arch extends from Nice on the western Mediterranean to Trieste on the Adriatic and Vienna at the beginning of the Pannonian Basin. The mountains were formed over tens of millions of years as the African and Eurasian tectonic plates collided.
Geometric medianIn geometry, the geometric median of a discrete set of sample points in a Euclidean space is the point minimizing the sum of distances to the sample points. This generalizes the median, which has the property of minimizing the sum of distances for one-dimensional data, and provides a central tendency in higher dimensions. It is also known as the 1-median, spatial median, Euclidean minisum point, or Torricelli point. The geometric median is an important estimator of location in statistics, where it is also known as the L1 estimator (after the L1 norm).
Bias of an estimatorIn statistics, the bias of an estimator (or bias function) is the difference between this estimator's expected value and the true value of the parameter being estimated. An estimator or decision rule with zero bias is called unbiased. In statistics, "bias" is an property of an estimator. Bias is a distinct concept from consistency: consistent estimators converge in probability to the true value of the parameter, but may be biased or unbiased; see bias versus consistency for more.
MonthA month is a unit of time, used with calendars, that is approximately as long as a natural orbital period of the Moon; the words month and Moon are cognates. The traditional concept arose with the cycle of Moon phases; such lunar months ("lunations") are synodic months and last approximately 29.53 days, making for roughly 12.37 such months in one Earth year. From excavated tally sticks, researchers have deduced that people counted days in relation to the Moon's phases as early as the Paleolithic age.
