Cluster samplingIn statistics, cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population. It is often used in marketing research. In this sampling plan, the total population is divided into these groups (known as clusters) and a simple random sample of the groups is selected. The elements in each cluster are then sampled. If all elements in each sampled cluster are sampled, then this is referred to as a "one-stage" cluster sampling plan.
Test automationIn software testing, test automation is the use of software separate from the software being tested to control the execution of tests and the comparison of actual outcomes with predicted outcomes. Test automation can automate some repetitive but necessary tasks in a formalized testing process already in place, or perform additional testing that would be difficult to do manually. Test automation is critical for continuous delivery and continuous testing.
Survey samplingIn statistics, survey sampling describes the process of selecting a sample of elements from a target population to conduct a survey. The term "survey" may refer to many different types or techniques of observation. In survey sampling it most often involves a questionnaire used to measure the characteristics and/or attitudes of people. Different ways of contacting members of a sample once they have been selected is the subject of survey data collection.
InfectionAn infection is the invasion of tissues by pathogens, their multiplication, and the reaction of host tissues to the infectious agent and the toxins they produce. An infectious disease, also known as a transmissible disease or communicable disease, is an illness resulting from an infection. Infections can be caused by a wide range of pathogens, most prominently bacteria and viruses. Hosts can fight infections using their immune systems. Mammalian hosts react to infections with an innate response, often involving inflammation, followed by an adaptive response.
Data analysisData analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.
Emerging infectious diseaseAn emerging infectious disease (EID) is an infectious disease whose incidence has increased recently (in the past 20 years), and could increase in the near future. The minority that are capable of developing efficient transmission between humans can become major public and global concerns as potential causes of epidemics or pandemics. Their many impacts can be economic and societal, as well as clinical. EIDs have been increasing steadily since at least 1940.
1957–1958 influenza pandemicThe 1957–1958 Asian flu pandemic was a global pandemic of influenza A virus subtype H2N2 that originated in Guizhou in Southern China. The number of excess deaths caused by the pandemic is estimated to be 1–4 million around the world (1957–1958 and probably beyond), making it one of the deadliest pandemics in history. A decade later, a reassorted viral strain H3N2 further caused the Hong Kong flu pandemic (1968–1969). The first cases were reported in Guizhou of southern China, in 1956 or in early 1957.
Systematic samplingIn survey methodology, systematic sampling is a statistical method involving the selection of elements from an ordered sampling frame. The most common form of systematic sampling is an equiprobability method. In this approach, progression through the list is treated circularly, with a return to the top once the list ends. The sampling starts by selecting an element from the list at random and then every kth element in the frame is selected, where k, is the sampling interval (sometimes known as the skip): this is calculated as: where n is the sample size, and N is the population size.
Multistage samplingIn statistics, multistage sampling is the taking of samples in stages using smaller and smaller sampling units at each stage. Multistage sampling can be a complex form of cluster sampling because it is a type of sampling which involves dividing the population into groups (or clusters). Then, one or more clusters are chosen at random and everyone within the chosen cluster is sampled. Using all the sample elements in all the selected clusters may be prohibitively expensive or unnecessary.
COVID-19 testingCOVID-19 testing involves analyzing samples to assess the current or past presence of SARS-CoV-2. The two main types of tests detect either the presence of the virus or antibodies produced in response to infection. Molecular tests for viral presence through its molecular components are used to diagnose individual cases and to allow public health authorities to trace and contain outbreaks. Antibody tests (serology immunoassays) instead show whether someone once had the disease.
