The normal distribution, a very common probability density, useful because of the central limit theorem.
The normal distribution, a very common probability density, useful because of the central limit theorem.
Scatter plots are used in descriptive statistics to show the observed relationships between different variables, here using the Iris flower data set.
Gerolamo Cardano, a pioneer on the mathematics of probability.
Karl Pearson, a founder of mathematical statistics.
A least squares fit: in red the points to be fitted, in blue the fitted line.
Confidence intervals: the red line is true value for the mean in this example, the blue lines are random confidence intervals for 100 realizations.
In this graph the black line is probability distribution for the test statistic, the critical region is the set of values to the right of the observed data point (observed value of the test statistic) and the p-value is represented by the green area.
The confounding variable problem: X and Y may be correlated, not because there is causal relationship between them, but because both depend on a third variable Z. Z is called a confounding factor.
gretl, an example of an open source statistical package

In statistics, a population is a set of similar items or events which is of interest for some question or experiment.

- Statistical population

In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied.

- Statistics
The normal distribution, a very common probability density, useful because of the central limit theorem.

2 related topics

Alpha

World population distribution

Statistical parameter

World population distribution

In statistics, as opposed to its general use in mathematics, a parameter is any measured quantity of a statistical population that summarises or describes an aspect of the population, such as a mean or a standard deviation.

A visual representation of selecting a simple random sample

Sampling (statistics)

A visual representation of selecting a simple random sample
A visual representation of selecting a random sample using the systematic sampling technique
A visual representation of selecting a random sample using the stratified sampling technique
A visual representation of selecting a random sample using the cluster sampling technique

In statistics, quality assurance, and survey methodology, sampling is the selection of a subset (a statistical sample) of individuals from within a statistical population to estimate characteristics of the whole population.