Galaxy filamentIn cosmology, galaxy filaments are the largest known structures in the universe, consisting of walls of gravitationally bound galactic superclusters. These massive, thread-like formations can reach 80 megaparsecs h−1 (or of the order of 160 to 260 million light-years) and form the boundaries between voids. Galaxy filaments form the cosmic web and define the overall structure of the observable universe. Discovery of structures larger than superclusters began in the late-1980s. In 1987, astronomer R.
Statistical hypothesis testingA statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. Hypothesis testing allows us to make probabilistic statements about population parameters. While hypothesis testing was popularized early in the 20th century, early forms were used in the 1700s. The first use is credited to John Arbuthnot (1710), followed by Pierre-Simon Laplace (1770s), in analyzing the human sex ratio at birth; see .
Cosmos Redshift 7Cosmos Redshift 7 (also known as COSMOS Redshift 7, Galaxy Cosmos Redshift 7, Galaxy CR7 or CR7) is a high-redshift Lyman-alpha emitter galaxy. At a redshift z = 6.6, the galaxy is observed as it was about 800 million years after the Big Bang, during the epoch of reionisation. With a light travel time of 12.9 billion years, it is one of the oldest, most distant galaxies known. CR7 shows some of the expected signatures of Population III stars i.e. the first generation of stars produced during early galaxy formation.
Nuisance parameterIn statistics, a nuisance parameter is any parameter which is unspecified but which must be accounted for in the hypothesis testing of the parameters which are of interest. The classic example of a nuisance parameter comes from the normal distribution, a member of the location–scale family. For at least one normal distribution, the variance(s), σ2 is often not specified or known, but one desires to hypothesis test on the mean(s).
Five-number summaryThe five-number summary is a set of descriptive statistics that provides information about a dataset. It consists of the five most important sample percentiles: the sample minimum (smallest observation) the lower quartile or first quartile the median (the middle value) the upper quartile or third quartile the sample maximum (largest observation) In addition to the median of a single set of data there are two related statistics called the upper and lower quartiles.
Seven-number summaryIn descriptive statistics, the seven-number summary is a collection of seven summary statistics, and is an extension of the five-number summary. There are three similar, common forms. As with the five-number summary, it can be represented by a modified box plot, adding hatch-marks on the "whiskers" for two of the additional numbers. The following percentiles are (approximately) evenly spaced under a normally distributed variable: the 2nd percentile (better: 2.15%) the 9th percentile (better: 8.
