A tag is a keyword or label that categorizes your question with other, similar questions. Using the right tags makes it easier for others to find and answer your question.
| Type to find tags: |
| meta-analysis× 103 | reliability× 103 | terminology× 102 | matrix× 102 |
| scales× 101 |
inference× 99
Inference, in a statistical context, refers to drawing conclusions about a population from information about a sample from that population.
|
random-generation× 98 |
summary-statistics× 98
A brief numerical description of a set of data.
|
| proportion× 97 |
epidemiology× 97
the study of the distribution and spread of disease or illness at the population level.
|
aic× 96
AIC stands for the Akaike Information Criterion, which is one technique used to select the best model from a class of models using a penalized likelihood. A smaller AIC implies a better model.
|
psychometrics× 96
Psychometrics has evolved as a subfield of psychology to become the science of measurement of unobservable individual characteristics.
|
| software× 96 |
count-data× 95
non-negative integers representing whole amounts. When such data are the dependent variable in a regression, Poisson or negative binomial regression may be appropriate methods. One comm…
|
k-means× 95
a family of cluster analysis methods in which you specify the number of clusters you expect. This is as opposed to hierarchical cluster analysis methods.
|
lasso× 95
Is a form of regularization used in estimation of regression coefficients which shrinks coefficient estimates by penalizing their absolute value (i.e. the $L_1$ norm of the estimates). The LASSO is eq…
|
| normality× 93 | curve-fitting× 93 | effect-size× 92 | multicollinearity× 92 |
|
sem× 91
structural equation modeling, a multivariate technique popular in social sciences. It is based on formulating a set of linear relations between variables, some of which may be latent, and estimating t…
|
hmm× 90
used for modelling systems that are assumed to be Markov processes with hidden (i.e. unobserved) states.
|
assumptions× 90
Refers to the conditions under which a statistics procedure yields valid estimates and/or inference. Many statistical techniques require the assumption that the data are randomly sampled in some way. …
|
dimensionality-reduction× 89
Dimensionality reduction refers to techniques for reducing many variables into a smaller number while keeping as much information as possible. One prominent method is [tag pca]
|
|
power-analysis× 89
An inquiry into the quality of a statistical test by calculating the power - the probability of rejecting the null hypothesis given that it is false - under certain circumstances. Power analysis is of…
|
sample× 89
a subset of a population. Statistics, in general, is concerned with using samples to make inference about the parameters governing a larger (possibly infinite) population.
|
roc× 88
Receiver Operating Characteristic, also known as ROC curve.
|
binary-data× 87
Refers to any data that can take on only one of two values. Common analysis tools for binary data and their relationship to covariates include logistic and probit regression.
|
| contingency-tables× 87 | fitting× 86 | robust× 86 |
quantiles× 86
The quantiles of a distribution refer to points on its cumulative distribution function. Some common quantiles are quartiles and percentiles.
|
|
logit× 85
A name given to the log-odds function, which maps probabilities to the real line.
|
mixture× 85
one that is written as a convex combination of other distributions.
|
histogram× 84
a graphical representation of the frequencies of a continuous variable. The variable is divided into bins and a bar is drawn for each bin, proportional to its frequency in the data.
|
large-data× 82
difficult to process and manage because their size are usually bigger than the limits software can normally deal with.
|
