Simple random sampleIn statistics, a simple random sample (or SRS) is a subset of individuals (a sample) chosen from a larger set (a population) in which a subset of individuals are chosen randomly, all with the same probability. It is a process of selecting a sample in a random way. In SRS, each subset of k individuals has the same probability of being chosen for the sample as any other subset of k individuals. A simple random sample is an unbiased sampling technique. Simple random sampling is a basic type of sampling and can be a component of other more complex sampling methods.
Sleep deprivationSleep deprivation, also known as sleep insufficiency or sleeplessness, is the condition of not having adequate duration and/or quality of sleep to support decent alertness, performance, and health. It can be either chronic or acute and may vary widely in severity. Acute sleep deprivation is when an individual sleeps less than usual or does not sleep at all for a short period of time – normally lasting one to two days but tends to follow the sleepless pattern for longer with no outside factors in play.
Sample mean and covarianceThe sample mean (sample average) or empirical mean (empirical average), and the sample covariance or empirical covariance are statistics computed from a sample of data on one or more random variables. The sample mean is the average value (or mean value) of a sample of numbers taken from a larger population of numbers, where "population" indicates not number of people but the entirety of relevant data, whether collected or not. A sample of 40 companies' sales from the Fortune 500 might be used for convenience instead of looking at the population, all 500 companies' sales.
Sleep in animalsSleep in animals refers to a behavioral and physiological state characterized by altered consciousness, reduced responsiveness to external stimuli, and homeostatic regulation observed in various animals. Sleep has been observed in mammals, birds, reptiles, amphibians, and some fish, and, in some form, in insects and even in simpler animals such as nematodes. The internal circadian clock promotes sleep at night for diurnal organisms (such as humans) and in the day for nocturnal organisms (such as rodents).
Sampling (statistics)In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. Statisticians attempt to collect samples that are representative of the population. Sampling has lower costs and faster data collection compared to recording data from the entire population, and thus, it can provide insights in cases where it is infeasible to measure an entire population.
AnthropometryAnthropometry () refers to the measurement of the human individual. An early tool of physical anthropology, it has been used for identification, for the purposes of understanding human physical variation, in paleoanthropology and in various attempts to correlate physical with racial and psychological traits. Anthropometry involves the systematic measurement of the physical properties of the human body, primarily dimensional descriptors of body size and shape.
Asymptotic theory (statistics)In statistics, asymptotic theory, or large sample theory, is a framework for assessing properties of estimators and statistical tests. Within this framework, it is often assumed that the sample size n may grow indefinitely; the properties of estimators and tests are then evaluated under the limit of n → ∞. In practice, a limit evaluation is considered to be approximately valid for large finite sample sizes too. Most statistical problems begin with a dataset of size n.
Polyphasic sleepPolyphasic sleep is the practice of sleeping during multiple periods over the course of 24 hours, in contrast to monophasic sleep, which is one period of sleep within 24 hours. Biphasic (or diphasic, bifurcated, or bimodal) sleep refers to two periods, while polyphasic usually means more than two. Segmented sleep and divided sleep may refer to polyphasic or biphasic sleep, but may also refer to interrupted sleep, where the sleep has one or several shorter periods of wakefulness, as was the norm for night sleep in pre-industrial societies.
Predictive modellingPredictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place. In many cases, the model is chosen on the basis of detection theory to try to guess the probability of an outcome given a set amount of input data, for example given an email determining how likely that it is spam.
Nerve injuryNerve injury is an injury to nervous tissue. There is no single classification system that can describe all the many variations of nerve injuries. In 1941, Seddon introduced a classification of nerve injuries based on three main types of nerve fiber injury and whether there is continuity of the nerve. Usually, however, peripheral nerve injuries are classified in five stages, based on the extent of damage to both the nerve and the surrounding connective tissue, since supporting glial cells may be involved.
Statistical inferenceStatistical inference is the process of using data analysis to infer properties of an underlying distribution of probability. Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is sampled from a larger population. Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population.
Dependent and independent variablesDependent and independent variables are variables in mathematical modeling, statistical modeling and experimental sciences. Dependent variables are studied under the supposition or demand that they depend, by some law or rule (e.g., by a mathematical function), on the values of other variables. Independent variables, in turn, are not seen as depending on any other variable in the scope of the experiment in question. In this sense, some common independent variables are time, space, density, mass, fluid flow rate, and previous values of some observed value of interest (e.
