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  2. Homogeneity and heterogeneity (statistics) - Wikipedia

    en.wikipedia.org/wiki/Homogeneity_and...

    In statistics, a sequence of random variables is homoscedastic (/ ˌ h oʊ m oʊ s k ə ˈ d æ s t ɪ k /) if all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity, also known as heterogeneity of variance.

  3. Homoscedasticity and heteroscedasticity - Wikipedia

    en.wikipedia.org/wiki/Homoscedasticity_and...

    In statistics, a sequence of random variables is homoscedastic (/ ˌ h oʊ m oʊ s k ə ˈ d æ s t ɪ k /) if all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity, also known as heterogeneity of variance.

  4. Glossary of probability and statistics - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_probability...

    Also confidence coefficient. A number indicating the probability that the confidence interval (range) captures the true population mean. For example, a confidence interval with a 95% confidence level has a 95% chance of capturing the population mean. Technically, this means that, if the experiment were repeated many times, 95% of the CIs computed at this level would contain the true population ...

  5. Cross-sectional data - Wikipedia

    en.wikipedia.org/wiki/Cross-sectional_data

    In statistics and econometrics, cross-sectional data is a type of data collected by observing many subjects (such as individuals, firms, countries, or regions) at a single point or period of time. Analysis of cross-sectional data usually consists of comparing the differences among selected subjects, typically with no regard to differences in time.

  6. Latent and observable variables - Wikipedia

    en.wikipedia.org/wiki/Latent_and_observable...

    Other latent variables correspond to abstract concepts, like categories, behavioral or mental states, or data structures. The terms hypothetical variables or hypothetical constructs may be used in these situations. The use of latent variables can serve to reduce the dimensionality of data. Many observable variables can be aggregated in a model ...

  7. Overdispersion - Wikipedia

    en.wikipedia.org/wiki/Overdispersion

    In statistics, overdispersion is the presence of greater variability (statistical dispersion) in a data set than would be expected based on a given statistical model.. A common task in applied statistics is choosing a parametric model to fit a given set of empirical observations.

  8. Data transformation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Data_transformation...

    The logarithm is often favored because it is easy to interpret its result in terms of "fold changes". The logarithm also has a useful effect on ratios. If we are comparing positive quantities X and Y using the ratio X / Y , then if X < Y , the ratio is in the interval (0,1), whereas if X > Y , the ratio is in the half-line (1,∞), where the ...

  9. Cointegration - Wikipedia

    en.wikipedia.org/wiki/Cointegration

    In econometrics, cointegration is a statistical property describing a long-term, stable relationship between two or more time series variables, even if those variables themselves are individually non-stationary (i.e., they have trends). This means that despite their individual fluctuations, the variables move together in the long run, anchored ...