Summary statisticsIn descriptive statistics, summary statistics are used to summarize a set of observations, in order to communicate the largest amount of information as simply as possible. Statisticians commonly try to describe the observations in a measure of location, or central tendency, such as the arithmetic mean a measure of statistical dispersion like the standard mean absolute deviation a measure of the shape of the distribution like skewness or kurtosis if more than one variable is measured, a measure of statistical dependence such as a correlation coefficient A common collection of order statistics used as summary statistics are the five-number summary, sometimes extended to a seven-number summary, and the associated box plot.
Logistic regressionIn statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place by having the log-odds for the event be a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (the coefficients in the linear combination).
KneeIn humans and other primates, the knee joins the thigh with the leg and consists of two joints: one between the femur and tibia (tibiofemoral joint), and one between the femur and patella (patellofemoral joint). It is the largest joint in the human body. The knee is a modified hinge joint, which permits flexion and extension as well as slight internal and external rotation. The knee is vulnerable to injury and to the development of osteoarthritis. It is often termed a compound joint having tibiofemoral and patellofemoral components.
Lack-of-fit sum of squaresIn statistics, a sum of squares due to lack of fit, or more tersely a lack-of-fit sum of squares, is one of the components of a partition of the sum of squares of residuals in an analysis of variance, used in the numerator in an F-test of the null hypothesis that says that a proposed model fits well. The other component is the pure-error sum of squares. The pure-error sum of squares is the sum of squared deviations of each value of the dependent variable from the average value over all observations sharing its independent variable value(s).
Multilevel modelMultilevel models (also known as hierarchical linear models, linear mixed-effect model, mixed models, nested data models, random coefficient, random-effects models, random parameter models, or split-plot designs) are statistical models of parameters that vary at more than one level. An example could be a model of student performance that contains measures for individual students as well as measures for classrooms within which the students are grouped.
Quadrants and regions of abdomenThe human abdomen is divided into quadrants and regions by anatomists and physicians for the purposes of study, diagnosis, and treatment. The division into four quadrants allows the localisation of pain and tenderness, scars, lumps, and other items of interest, narrowing in on which organs and tissues may be involved. The quadrants are referred to as the left lower quadrant, left upper quadrant, right upper quadrant and right lower quadrant. These terms are not used in comparative anatomy, since most other animals do not stand erect.
Big BangThe Big Bang event is a physical theory that describes how the universe expanded from an initial state of high density and temperature. Various cosmological models of the Big Bang explain the evolution of the observable universe from the earliest known periods through its subsequent large-scale form. These models offer a comprehensive explanation for a broad range of observed phenomena, including the abundance of light elements, the cosmic microwave background (CMB) radiation, and large-scale structure.
Knee painKnee pain is pain in or around the knee. The knee joint consists of an articulation between four bones: the femur, tibia, fibula and patella. There are four compartments to the knee. These are the medial and lateral tibiofemoral compartments, the patellofemoral compartment and the superior tibiofibular joint. The components of each of these compartments can experience repetitive strain, injury or disease. Running long distance can cause pain to the knee joint, as it is a high-impact exercise.
PeritonitisPeritonitis is inflammation of the localized or generalized peritoneum, the lining of the inner wall of the abdomen and cover of the abdominal organs. Symptoms may include severe pain, swelling of the abdomen, fever, or weight loss. One part or the entire abdomen may be tender. Complications may include shock and acute respiratory distress syndrome. Causes include perforation of the intestinal tract, pancreatitis, pelvic inflammatory disease, stomach ulcer, cirrhosis, a ruptured appendix or even a perforated gallbladder.
EpigastriumIn anatomy, the epigastrium (or epigastric region) is the upper central region of the abdomen. It is located between the costal margins and the subcostal plane. Pain may be referred to the epigastrium from damage to structures derived from the foregut. The epigastrium is one of the nine regions of the abdomen, along with the right and left hypochondria, right and left lateral regions (lumbar areas or flanks), right and left inguinal regions (or fossae), and the umbilical and pubic regions.
DataIn common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.
Imputation (statistics)In statistics, imputation is the process of replacing missing data with substituted values. When substituting for a data point, it is known as "unit imputation"; when substituting for a component of a data point, it is known as "item imputation". There are three main problems that missing data causes: missing data can introduce a substantial amount of bias, make the handling and analysis of the data more arduous, and create reductions in efficiency.
