What is the breakdown point of an estimator?

A breakdown point is the point after which an estimator becomes useless. It is a measure of robustness; The larger the breakdown point, the better the estimator. If an estimator has a high breakdown point, it may be called a resistant statistic.

What is a breakdown value?

The breakdown value is a popular measure of the robustness of an estimator against outlying observations. Roughly speaking, it indicates the smallest fraction of contaminants in a sample that causes the estimator to break down, that is, to take on values that are arbitrarily bad or meaningless.

What is the value of an estimator called?

The value of the estimator is referred to as a point estimate. There are several different types of estimators. If the expected value of the estimator equals the population parameter, the estimator is an unbiased estimator.

What is the breakdown point?

breakdown point (plural breakdown points) (statistics, of an estimator) The number or proportion of arbitrarily large or small extreme values that must be introduced into a batch or sample to cause the estimator to yield an arbitrarily large result.

Is the Iqr robust?

In statistics, robust measures of scale are methods that quantify the statistical dispersion in a sample of numerical data while resisting outliers. The most common such robust statistics are the interquartile range (IQR) and the median absolute deviation (MAD).

What does se mean mean in statistics?

standard error
The standard error (SE) of a statistic is the approximate standard deviation of a statistical sample population. The standard error is a statistical term that measures the accuracy with which a sample distribution represents a population by using standard deviation.

What are the two most important properties of an estimator?

Many methods have been devised for estimating parameters that may provide estimators satisfying these properties. The two important methods are the least square method and the method of maximum likelihood.

What makes data robust?

Robust statistics, therefore, are any statistics that yield good performance when data is drawn from a wide range of probability distributions that are largely unaffected by outliers or small departures from model assumptions in a given dataset. In other words, a robust statistic is resistant to errors in the results.

Is variance a robust measure?

The most common such robust statistics are the interquartile range (IQR) and the median absolute deviation (MAD). These are contrasted with conventional or non-robust measures of scale, such as sample variance or standard deviation, which are greatly influenced by outliers.