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independently. Many types of sampling fall under the plot sampling category including quadrant sampling, strip sampling, and many others. Each considers
Plot_sampling
Group of statistical methods
species. A variety of methods are used in abundance sampling: mark-recapture, plot sampling, distance sampling. Terrestrial and marine habitats require different
Abundance_estimation
Comparison of two distributions
statistics, a Q–Q plot (quantile–quantile plot) is a probability plot, a graphical method for comparing two probability distributions by plotting their quantiles
Q–Q_plot
Selection of data points in statistics
of the population. When sampling, statisticians aim towards collecting an unbiased group, and to do it judiciously. Sampling has lower costs and faster
Sampling_(statistics)
Data visualization
dataset may be plotted as individual points beyond the whiskers on the box plot. Box plots are non-parametric: they display variation in samples of a statistical
Box_plot
Barycentric plot on three variables
A ternary plot, ternary graph, triangle plot, simplex plot, or Gibbs triangle is a barycentric plot on three variables which sum to a constant. It graphically
Ternary_plot
Method of plotting numeric data
interquartile range; and possibly all sample points, if the number of samples is not too high. While a box plot shows a summary statistics such as median
Violin_plot
Accelerated failure time model Acceptable quality limit Acceptance sampling Accidental sampling Accuracy and precision Accuracy paradox Acquiescence bias Actuarial
List_of_statistics_articles
Sampling from a population which can be partitioned into subpopulations
In statistics, stratified sampling is a method of sampling from a population which can be partitioned into subpopulations. In statistical surveys, when
Stratified_sampling
Statistical sampling technique
This sampling scheme does not require more samples for more dimensions (variables); this independence is one of the main advantages of this sampling scheme
Latin_hypercube_sampling
Data visualization
A Bland–Altman plot (or Bland–Altman difference plot) in analytical chemistry or biomedicine is a method of data plotting used in analyzing the agreement
Bland–Altman_plot
Statistical considerations on how many observations to make
complicated sampling techniques, such as stratified sampling, the sample can often be split up into sub-samples. Typically, if there are H such sub-samples (from
Sample_size_determination
Statistical property
intervals. The sampling distribution of a mean is generated by repeated sampling from the same population and recording the sample mean per sample. This forms
Standard_error
Reuse of sound recording in another recording
chop sampling; sampling a short, isolated sound such as a drum hit or vocal snippet is known as one-shot sampling. Samples are distributed in sample libraries
Sampling_(music)
Probability distribution of the possible sample outcomes
contexts, only one sample (i.e., a set of observations) is observed, but the sampling distribution can be found theoretically. Sampling distributions are
Sampling_distribution
Plot using the dispersal of scattered dots to show the relationship between variables
A scatter plot, also called a scatterplot, scatter graph, scatter chart, scattergram, or scatter diagram, is a type of plot or mathematical diagram using
Scatter_plot
Sampling methodology in statistics
In statistics, cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population
Cluster_sampling
Story writing technique
A plot device or plot mechanism is any technique in a narrative used to move the plot forward. A clichéd plot device may annoy the reader and a contrived
Plot_device
Single measure of some attribute of a sample
in a sample which is considered for a statistical purpose. Statistical purposes include estimating a population parameter, describing a sample, or evaluating
Statistic
Statistical method
error, etc.) to sample estimates. This technique allows estimation of the sampling distribution of almost any statistic using random sampling methods. Bootstrapping
Bootstrapping_(statistics)
Statistical measure of how far values spread from their average
statistical inference, hypothesis testing, goodness of fit, and Monte Carlo sampling. The variance of a random variable X {\displaystyle X} is the expected
Variance
Graphical display of scientific results
Wikimedia Commons has media related to Forest plots. A forest plot, also known as a blobbogram, is a graphical display of estimated results from a number
Forest_plot
Systematic collection of information about a forested area for assessment or analysis
computer software. Plots are samples of the forest being inventoried and so are selected according to what is looked for. Simple random sampling: A computer
Forest_inventory
Technique to assess species richness
created by randomly re-sampling the pool of N samples multiple times and then plotting the average number of species found in each sample (1,2, ... N). "Thus
Rarefaction_(ecology)
Type of chart
decisions. The chart on the right contains the star plots of 15 cars. The variable list for the sample star plot is: Price Mileage (MPG) 1978 Repair Record (1
Radar_chart
Unit of information
Optimal design Population Replication Sample size determination Statistic Statistical power Survey methodology Sampling Cluster Stratified Opinion poll Questionnaire
Data
Distribution function associated with the empirical measure of a sample
quantiles from a sample Frequency (statistics) Empirical likelihood Kaplan–Meier estimator for censored processes Survival function Q–Q plot A modern introduction
Empirical distribution function
Empirical_distribution_function
Numerical technique
perform a Monte Carlo integration, such as uniform sampling, stratified sampling, importance sampling, sequential Monte Carlo (also known as a particle
Monte_Carlo_integration
Diagram in computational biology
measurements taken in two samples, by transforming the data onto M (log ratio) and A (mean average) scales, then plotting these values. Though originally
MA_plot
Digital signal sample rate converter
between the high sampling rate of fs used by the integrator stages and the low sampling rate of fsR used by the comb stages. At the high sampling rate of fs
Cascaded integrator–comb filter
Cascaded_integrator–comb_filter
Statistical model validation technique
random sub-sampling validation tends towards that of leave-p-out cross-validation. In a stratified variant of this approach, the random samples are generated
Cross-validation_(statistics)
Measure of statistical dispersion
robust measure of scale. It can be clearly visualized by the box on a box plot. Unlike total range, the interquartile range has a breakdown point of 25%
Interquartile_range
a similar manner as an angle gauge in variable-radius plot sampling. In this type of sampling, the wedge prism is used to estimate basal area of a group
Wedge_prism
American metalcore band
The Plot in You is an American metalcore band formed in Hancock County, Ohio in 2010. Originally a side project of former Before Their Eyes member Landon
The_Plot_in_You
Type of sampling strategy
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
Multistage_sampling
Series of questions for gathering information
collected using sound sampling techniques, often the results can be non-representative of the population—as such a good sample is critical to getting
Questionnaire
Data graphic
A ridgeline plot (also known as a joyplot) is a series of line plots that are combined by vertical stacking to allow the easy visualization of changes
Ridgeline_plot
Method of statistical sampling
clear distinctions during sampling. This sampling method should be distinguished from cluster sampling, where a simple random sample of several entire clusters
Stratified_randomization
Overview of and topical guide to statistics
Statistical survey Opinion poll Sampling theory Sampling distribution Stratified sampling Quota sampling Cluster sampling Biased sample Spectrum bias Survivorship
Outline_of_statistics
Probability plot which compares two cumulative distribution functions
In statistics, a P–P plot (probability–probability plot or percent–percent plot or P value plot) is a probability plot for assessing how closely two data
P–P_plot
Kth smallest value in a statistical sample
X 2 , … , X n {\displaystyle X_{1},X_{2},\ldots ,X_{n}} can arise by sampling from more than one population. Then we consider the case where they are
Order_statistic
Term in statistical hypothesis testing
factors lead to an expected amount of sampling error. A smaller sampling error could be obtained by larger sample sizes from a less variability population
Power_(statistics)
Class of statistical tests
plot, a quantile-quantile plot (QQ plot) of the standardized data against the standard normal distribution. Here the correlation between the sample data
Normality_test
discussed on this page are split-plot and strip-plot designs. The objective of an experiment with this type of sampling plan is generally to reduce the
Restricted_randomization
Process of using data analysis for predicting population data from sample data
also of importance: in survey sampling, use of sampling without replacement ensures the exchangeability of the sample with the population; in randomized
Statistical_inference
Statistical hypothesis test
or the Brown–Forsythe test; or assessable graphically using a Q–Q plot). If the sample sizes in the two groups being compared are equal, Student's original
Student's_t-test
Value that appears most often in a set of data
argmaxxi P(X = xi). In other words, it is the value that is most likely to be sampled. Like the statistical mean and median, the mode is a summary statistic
Mode_(statistics)
Graphical technique for data sets
structure. Drain Plot. Biplot Bland–Altman plot Box plot Carpet plot Contour plot Logarithmic plot Parallel Category Plot Funnel plot : This is a useful
Plot_(graphics)
Test of normality in frequentist statistics
test Normal probability plot Shapiro, S. S.; MIRAS, M. B. (1965). "An analysis of variance test for normality (complete samples)". Biometrika. 52 (3–4):
Shapiro–Wilk_test
Relative measure of dispersion expressed as the ratio of standard deviation to the mean
for the coefficient of variation. Notably, Lehmann (1986) derived the sampling distribution for the coefficient of variation using a non-central t-distribution
Coefficient_of_variation
Range to estimate an unknown parameter
(CI) determines lower and upper bounds likely to contain (in repeated sampling) the true value of an unknown statistical parameter, such as a population
Confidence_interval
Statistical hypothesis test
sampling distribution (if the null hypothesis is true) of the test statistic approximates a chi-squared distribution more and more closely as sample sizes
Chi-squared_test
Type of statistics
of exploratory data analysis: an example of such a technique is the box plot. In the business world, descriptive statistics provides a useful summary
Descriptive_statistics
Graphical technique in statistics
is a sample of size 50 from a uniform distribution, plotted as both a histogram, and a normal probability plot. Normal probability plot of a sample from
Normal_probability_plot
Greatest and least values in a statistical data sample
associated box plot. The minimum and the maximum value are the first and last order statistics (often denoted X(1) and X(n) respectively, for a sample size of
Sample_maximum_and_minimum
Diagnostic plot in multivariate statistics
multivariate statistics, a scree plot is a line plot of the eigenvalues of factors or principal components in an analysis. The scree plot is used to determine the
Scree_plot
Statistical phenomenon
to mediocrity) is the phenomenon where if one sample of a random variable is extreme, the next sampling of the same random variable is likely to be closer
Regression_toward_the_mean
Type of graph used in research
A funnel plot is a graph designed to check for the existence of publication bias; funnel plots are commonly used in systematic reviews and meta-analyses
Funnel_plot
How many standard deviations apart from the mean an observed datum is
belongs; if one only has a sample of observations from the population, then the analogous computation using the sample mean and sample standard deviation yields
Standard_score
Statistics concept
and systematic errors Reduced chi-squared statistic Regression dilution Sampling error Standard error Studentized residual Type I and type II errors Kennedy
Errors_and_residuals
Statistical measure of variability
robust or outlier-resistant measure of the variability of a univariate sample of quantitative data. For a univariate data set X1, X2, ..., Xn, the MAD
Median_absolute_deviation
Numerical measure of a statistical relationship between variables
may be two columns of a given data set of observations, often called a sample, or two components of a multivariate random variable with a known distribution
Correlation_coefficient
Study of collection and analysis of data
experiment designs and survey samples. Random sampling assures that inferences and conclusions can reasonably extend from the sample to the population as a whole
Statistics
Type of exploratory graph used in statistics
score plot with a loading plot. A biplot allows information on both samples and variables of a data matrix to be displayed graphically. Samples are displayed
Biplot
Measure of variation in statistics
{\left({\frac {N-1}{2}}\right)}}}.} This arises because the sampling distribution of the sample standard deviation follows a (scaled) chi distribution, and
Standard_deviation
Probabilistic problem-solving algorithm
use adaptive routines such as stratified sampling, recursive stratified sampling, adaptive umbrella sampling or the VEGAS algorithm. A similar approach
Monte_Carlo_method
Sampling technique used in physics
Umbrella sampling is a technique in computational physics and chemistry, used to improve sampling of a system (or different systems) where ergodicity is
Umbrella_sampling
Processes that maintain quality at a constant level
Optimal design Population Replication Sample size determination Statistic Statistical power Survey methodology Sampling Cluster Stratified Opinion poll Questionnaire
Quality_control
Human research survey of public opinion
based on samples of populations are subject to sampling error which reflects the effects of chance and uncertainty in the sampling process. Sampling polls
Opinion_poll
Statistical hypothesis test
(statistics) Homogeneity of variance Independence of errors and random sampling The hypothesis that a proposed regression model fits the data well. See
F-test
Maximum frequency of non-aliased component upon sampling
this example, fs is the sampling rate, and 0.5 cycles/sample × fs is the corresponding Nyquist frequency. The black dot plotted at 0.6 fs represents the
Nyquist_frequency
Concept in inferential statistics
from a sample, this means that the rejection region comprises 5% of the sampling distribution. These 5% can be allocated to one side of the sampling distribution
Statistical_significance
Frequency divided by a characteristic frequency
{\displaystyle f} ) and a constant frequency associated with a system (such as a sampling rate, f s {\displaystyle f_{s}} ). Some software applications require normalized
Normalized frequency (signal processing)
Normalized_frequency_(signal_processing)
Complete set of items that share at least one property in common
original on 2005-02-09. Levy, Paul S.; Lemeshow, Stanley (2013-06-07). Sampling of Populations: Methods and Applications. John Wiley & Sons. ISBN 978-1-118-62731-0
Statistical_population
Statistical test comparing two probability distributions
test whether a sample came from a given reference probability distribution (one-sample K–S test), or to test whether or not two samples came from the same
Kolmogorov–Smirnov_test
Type of chart
lengths proportional to the values that they represent. The bars can be plotted vertically or horizontally. A vertical bar chart is sometimes called a
Bar_chart
Chart used in statistical quality control
observations are taken for each sample Accounting for differences in the number of observations from sample to sample Sampling requires some careful consideration
P-chart
Nonparametric test of the null hypothesis
two-sample problem is the median of all possible differences between an observation in the first sample and an observation in the second sample. Otherwise
Mann–Whitney_U_test
Graphical representation of the distribution of numerical data
x-axis are all 1, then a histogram is identical to a relative frequency plot. Histograms are sometimes confused with bar charts. In a histogram, each
Histogram
Experiment methodology
variable. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics. A/B testing is employed
A/B_testing
Statistic measuring inter-rater agreement for categorical items
"The Kappa Statistic in Reliability Studies: Use, Interpretation, and Sample Size Requirements". Physical Therapy. 85 (3): 257–268. doi:10.1093/ptj/85
Cohen's_kappa
Type of average of a collection of numbers
Greek letter μ. If the data set is a statistical sample (a subset of the population), it is called the sample mean (which for a data set X is denoted as X‾)
Arithmetic_mean
American born ecologist (1924–1994)
doi:10.2307/1932009 Cooper, C. F. 1963. An Evaluation of Variable Plot Sampling in Shrub and Herbaceous Vegetation. Ecology 44:565–569. doi:10.2307/1932536
Charles_F._Cooper_(ecologist)
Non-parametric method for testing whether samples originate from the same distribution
whether samples originate from the same distribution. It is used for comparing two or more independent samples of equal or different sample sizes. It
Kruskal–Wallis_test
Generates a forecast of future values of a time series
{\Delta T}{\ln(1-\alpha )}}} where Δ T {\displaystyle \Delta T} is the sampling time interval of the discrete time implementation. Some math libraries
Exponential_smoothing
Fundamental theorem in probability theory and statistics
random sampling of any variable, rather than to the mean values (or sums) of iid random variables extracted from a population by repeated sampling. That
Central_limit_theorem
Dirichlet distribution, a generalization of the beta distribution. The Ewens's sampling formula is a probability distribution on the set of all partitions of an
List of probability distributions
List_of_probability_distributions
Measure of linear correlation
on the value of the sample correlation coefficient r. The other aim is to derive a confidence interval that, on repeated sampling, has a given probability
Pearson correlation coefficient
Pearson_correlation_coefficient
Diagnostic plot of binary classifier ability
A receiver operating characteristic curve, or ROC curve, is a graphical plot that illustrates the performance of a binary classifier model (although it
Receiver operating characteristic
Receiver_operating_characteristic
Free and open-source statistical program
that can be activated via the module menu: Acceptance Sampling: Methods for acceptance sampling and a quality control setting. Audit: Statistical methods
JASP
Statistical measure to determine how suited data is for factor analysis
Measure of Sampling Adequacy (MSA) of factor analytic data matrices in 1970. Kaiser and Rice then modified it in 1974. The measure of sampling adequacy
Kaiser–Meyer–Olkin_test
Number of values in the final calculation of a statistic that are free to vary
complex survey sampling design, the (lower bound of) degrees of freedom of the sampling design is usually given as (number of primary sampling units) - (number
Degrees of freedom (statistics)
Degrees_of_freedom_(statistics)
Type of statistical measure over subsets of a dataset
When calculating the next mean 𝑆𝑀𝐴k,next with the same sampling width k the range from n−k+2 to n+1 is considered. A new value pn+1 comes
Moving_average
Compilation of information about a given population
for designing sample surveys by providing a sampling frame, such as an address register. Census counts are necessary to adjust samples to be representative
Census
Interpretation of probability
experiments. Procedures for testing hypotheses about probabilities (using finite samples) are due to Ramsey (1931) and de Finetti (1931, 1937, 1964, 1970). Both
Bayesian_probability
Fourth standardized moment in statistics
exponential distribution, red curve (two straight lines in the log-scale plot), excess kurtosis = 3 S: hyperbolic secant distribution, orange curve, excess
Kurtosis
Measure of the asymmetry of random variables
that can be used in conjunction with the histogram and the normal quantile plot to characterize the data or distribution. Skewness indicates the direction
Skewness
Distinction between nominal, ordinal, interval and ratio variables
Optimal design Population Replication Sample size determination Statistic Statistical power Survey methodology Sampling Cluster Stratified Opinion poll Questionnaire
Level_of_measurement
Data analysis approach in frequentist statistics
interaction of the effect size, the sample size (all things being equal a larger sample size produces a smaller p-value) and sampling error. At low power, simulation
Estimation_statistics
Statistical property
standard errors instead of using GLS, as GLS can exhibit strong bias in small samples if the actual skedastic function is unknown. Because heteroscedasticity
Homoscedasticity and heteroscedasticity
Homoscedasticity_and_heteroscedasticity
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