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  2. Subject-expectancy effect - Wikipedia

    en.wikipedia.org/wiki/Subject-expectancy_effect

    In scientific research and psychotherapy, the subject-expectancy effect, is a form of reactivity that occurs when a research subject expects a given result and therefore unconsciously affects the outcome, or reports the expected result.

  3. Test case - Wikipedia

    en.wikipedia.org/wiki/Test_case

    An expected result or expected outcome is usually given. Additional information that may be included: [7] Test case ID - A unique identifier for the test case. Description/summary - The test case objective. Test steps - The exact steps to perform. Expected result - The expected outcome and how to determine whether it has been realized. Actual ...

  4. Expected value - Wikipedia

    en.wikipedia.org/wiki/Expected_value

    To empirically estimate the expected value of a random variable, one repeatedly measures observations of the variable and computes the arithmetic mean of the results. If the expected value exists, this procedure estimates the true expected value in an unbiased manner and has the property of minimizing the sum of the squares of the residuals ...

  5. Mean squared error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_error

    To minimize MSE, the model could be more accurate, which would mean the model is closer to actual data. One example of a linear regression using this method is the least squares method —which evaluates appropriateness of linear regression model to model bivariate dataset , [ 6 ] but whose limitation is related to known distribution of the data.

  6. Software testing - Wikipedia

    en.wikipedia.org/wiki/Software_testing

    A test case normally consists of a unique identifier, requirement references from a design specification, preconditions, events, a series of steps (also known as actions) to follow, input, output, expected result, and the actual result. Clinically defined, a test case is an input and an expected result. [74]

  7. Bias of an estimator - Wikipedia

    en.wikipedia.org/wiki/Bias_of_an_estimator

    The expected loss is minimised when cnS 2 = <σ 2 >; this occurs when c = 1/(n − 3). Even with an uninformative prior, therefore, a Bayesian calculation may not give the same expected-loss minimising result as the corresponding sampling-theory calculation.

  8. Variance (accounting) - Wikipedia

    en.wikipedia.org/wiki/Variance_(accounting)

    When actual results are better than expected results given variance is described as favorable variance. In common use favorable variance is denoted by the letter F - usually in parentheses (F). When actual results are worse than expected results given variance is described as adverse variance, or unfavourable variance.

  9. Positive and negative predictive values - Wikipedia

    en.wikipedia.org/wiki/Positive_and_negative...

    The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.