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  2. Null hypothesis - Wikipedia

    en.wikipedia.org/wiki/Null_hypothesis

    A possible null hypothesis is that the mean male score is the same as the mean female score: H 0: μ 1 = μ 2. where H 0 = the null hypothesis, μ 1 = the mean of population 1, and μ 2 = the mean of population 2. A stronger null hypothesis is that the two samples have equal variances and shapes of their respective distributions.

  3. Type I and type II errors - Wikipedia

    en.wikipedia.org/wiki/Type_I_and_type_II_errors

    The results of such testing determine whether a particular set of results agrees reasonably (or does not agree) with the speculated hypothesis. On the basis that it is always assumed, by statistical convention, that the speculated hypothesis is wrong, and the so-called "null hypothesis" that the observed phenomena simply occur by chance (and ...

  4. False positives and false negatives - Wikipedia

    en.wikipedia.org/wiki/False_positives_and_false...

    In statistical hypothesis testing, the analogous concepts are known as type I and type II errors, where a positive result corresponds to rejecting the null hypothesis, and a negative result corresponds to not rejecting the null hypothesis. The terms are often used interchangeably, but there are differences in detail and interpretation due to ...

  5. Hypothesis - Wikipedia

    en.wikipedia.org/wiki/Hypothesis

    The hypothesis of Andreas Cellarius, showing the planetary motions in eccentric and epicyclical orbits. A hypothesis (pl.: hypotheses) is a proposed explanation for a phenomenon. A scientific hypothesis must be based on observations and make a testable and reproducible prediction about reality, in a process beginning with an educated guess or ...

  6. Misuse of statistics - Wikipedia

    en.wikipedia.org/wiki/Misuse_of_statistics

    (Fisher in The Design of Experiments) Many reasons for confusion exist including the use of double negative logic and terminology resulting from the merger of Fisher's "significance testing" (where the null hypothesis is never accepted) with "hypothesis testing" (where some hypothesis is always accepted).

  7. Wald test - Wikipedia

    en.wikipedia.org/wiki/Wald_test

    In statistics, the Wald test (named after Abraham Wald) assesses constraints on statistical parameters based on the weighted distance between the unrestricted estimate and its hypothesized value under the null hypothesis, where the weight is the precision of the estimate.

  8. Null distribution - Wikipedia

    en.wikipedia.org/wiki/Null_distribution

    Null distribution is a tool scientists often use when conducting experiments. The null distribution is the distribution of two sets of data under a null hypothesis. If the results of the two sets of data are not outside the parameters of the expected results, then the null hypothesis is said to be true. Null and alternative distribution

  9. Test statistic - Wikipedia

    en.wikipedia.org/wiki/Test_statistic

    The null hypothesis is that it does. Chi-squared tests of independence are used for deciding whether two variables are associated or are independent. The variables are categorical rather than numeric. It can be used to decide whether left-handedness is correlated with height (or not). The null hypothesis is that the variables are independent.