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  2. Null hypothesis - Wikipedia

    en.wikipedia.org/wiki/Null_hypothesis

    David Cox said, "How [the] translation from subject-matter problem to statistical model is done is often the most critical part of an analysis". [16] A statistical significance test is intended to test a hypothesis. If the hypothesis summarizes a set of data, there is no value in testing the hypothesis on that set of data.

  3. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    The p-value does not provide the probability that either the null hypothesis or its opposite is correct (a common source of confusion). [ 36 ] If the p -value is less than the chosen significance threshold (equivalently, if the observed test statistic is in the critical region), then we say the null hypothesis is rejected at the chosen level of ...

  4. Scale analysis (statistics) - Wikipedia

    en.wikipedia.org/wiki/Scale_analysis_(statistics)

    The item-total correlation approach is a way of identifying a group of questions whose responses can be combined into a single measure or scale. This is a simple approach that works by ensuring that, when considered across a whole population, responses to the questions in the group tend to vary together and, in particular, that responses to no individual question are poorly related to an ...

  5. Dummy variable (statistics) - Wikipedia

    en.wikipedia.org/wiki/Dummy_variable_(statistics)

    The variable could take on a value of 1 for males and 0 for females (or vice versa). In machine learning this is known as one-hot encoding. Dummy variables are commonly used in regression analysis to represent categorical variables that have more than two levels, such as education level or occupation.

  6. Loss aversion - Wikipedia

    en.wikipedia.org/wiki/Loss_aversion

    The results showed drastic differences between induced-value markets and goods markets. The median prices of buyers and sellers in induced-value markets matched almost every time leading to near perfect market efficiency, but goods markets sellers had much higher selling prices than buyers' buying prices. This effect was consistent over trials ...

  7. Statistical assumption - Wikipedia

    en.wikipedia.org/wiki/Statistical_assumption

    Statistical assumptions can be put into two classes, depending upon which approach to inference is used. Model-based assumptions. These include the following three types: Distributional assumptions. Where a statistical model involves terms relating to random errors, assumptions may be made about the probability distribution of these errors. [5]

  8. Dependent and independent variables - Wikipedia

    en.wikipedia.org/wiki/Dependent_and_independent...

    In mathematics, a function is a rule for taking an input (in the simplest case, a number or set of numbers) [5] and providing an output (which may also be a number). [5] A symbol that stands for an arbitrary input is called an independent variable, while a symbol that stands for an arbitrary output is called a dependent variable. [6]

  9. Base rate - Wikipedia

    en.wikipedia.org/wiki/Base_rate

    What is missing from these statistics is the relevant base rate information. The doctor should be asked, "Out of the number of people who test positive (base rate group), how many have cancer?" [ 6 ] In assessing the probability that a given individual is a member of a particular class, information other than the base rate needs to be accounted ...